Professor Melanie Hezzell
MA(Cantab.), VetMB(Cantab.), PhD(RVC), CertVDI, CertVC, MRCVS, DACVIM (Cardiology)
Expertise
I am a clinically active Veterinary Cardiologist. My research interests centre on the pathophysiology of cardiovascular disease, including genetic influences, remodelling, endothelial dysfunction and the cardiorenal syndrome.
Current positions
Professor of Veterinary Cardiology
Bristol Veterinary School
Contact
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Research interests
My research focuses particularly on the use of biomarkers in clinical veterinary practice. I am also involved in research investigating myocardial remodelling in valvular heart disease.
Projects and supervisions
Research projects
Do measurements of circulating fibrosis markers change with disease progression in canine myxomatous mitral valve disease?
Principal Investigator
Managing organisational unit
Bristol Medical School (THS)Dates
17/05/2022 to 30/06/2025
Remodelling in Canine Myxomatous Mitral Valve Disease
Principal Investigator
Managing organisational unit
Bristol Medical School (THS)Dates
01/04/2022 to 31/03/2026
Remodelling in Myxomatous Mitral Valve Disease: The Relationship between Inflammation and the Development of Fibrosis
Principal Investigator
Managing organisational unit
Bristol Medical School (THS)Dates
01/05/2021 to 30/04/2026
Thesis supervisions
Publications
Recent publications
01/06/2025Accelerometer-derived classifiers for early detection of degenerative joint disease in cats
Veterinary Journal
A Deep Learning Methodology for Screening New Natural Therapeutic Candidates for Pharmacological Cardioversion and Anticoagulation in the Treatment and Management of Atrial Fibrillation
Biomedicines
Anti-desmoglein 2 autoantibodies do not discriminate between control and arrhythmogenic right ventricular cardiomyopathy affected boxer dogs in the UK
Veterinary Record
Fatal consequences of feline coronavirus infection are associated with virus persistence and a distinct adaptive immune repertoire
Science Advances
Rapid Screening of Anticoagulation Compounds for Biological Target-Associated Adverse Effects Using a Deep-Learning Framework in the Management of Atrial Fibrillation
Bioengineering
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