Lactation mastitis is an inflammatory breast disease affecting 17-27% of Australian breastfeeding women that causes pain, fever and low milk supply. The challenges posed by this disease lead many women to use supplementary formula, or cease breastfeeding altogether leaving their infants at increased risk of respiratory and gastrointestinal diseases as babies, and non-communicable diseases including heart disease, obesity, diabetes, cancer, allergies, asthma, mental illness and chronic lung, liver and renal diseases as both children and adults. Our recent research has suggested that macrophages play a role in development of this disease. Our current research pursues new knowledge in how disease state develop in the breast. We explore revolutionary new concepts of how immune cells function in the breast, and how these cells affect breast disease development..
Gene expression profiling of breast cancer is a technology increasingly being adopted in the clinic as a personalised medicine approach to tailor treatment to individual patients. However, an underappreciated factor in premenopausal breast cancer diagnosis is that oestrogen and progesterone fluctuate dramatically during the menstrual cycle, and these hormones are likely to affect gene expression. Our research aims to determine whether fluctuation in oestrogen and progesterone associated with different stages of the menstrual cycle significantly affects gene expression profiles in breast cancers from premenopausal women..
Reducing breast cancer risk starts with developing a better understanding of how the disease develops. Breast density (also known as mammographic density) is the percentage of white and bright regions on a mammogram. Breast density is not related to how breasts look or feel and can only be assessed by mammogram. High breast density is both an independent risk factor for breast cancer and masks cancers on a mammogram. There is exciting potential for breast density to become a widespread health assessment tool, used to identify the women most at risk of breast cancer in order to intervene early and reduce that risk. Our research studies the underlying biology of breast density and how it affects the risk of breast cancer..
Machine learning is a form of artificial intelligence that enables computers to learn how to do complex tasks without being programmed by humans. This technology is driving what is known as the “fourth industrial revolution”. It has the potential to deliver massive benefits in biomedicine and we are only just starting to explore its capability. Working with experts in engineering, pathology, biology, radiology and artificial intelligence, we are developing new computational systems that aid in the accurate and efficient detection and diagnosis of breast cancer..
Coronary angiography is the clinical benchmark technique in the assessment of coronary artery disease with more than 6,000 performed in South Australia each year. Despite its diagnostic benefits in identifying the presence of coronary disease, its benefit to the patient has been less rigorously studied and will be the focus of this project. CADOSA is an internationally renowned clinical registry incorporating global links with organizations including the American College of Cardiology National Cardiovascular Data Registry and the International Consortium of Health Outcomes Measurement (ICHOM)..
Please also refer to Professor John Beltrame's University of Adelaide Researcher Profile. .
Projects available for honours and postgraduate students, who will be enrolled through the University of South Australia, include:.
The Viral Immunology Group has student projects available for Honours, Masters and PhD studies. The projects cover vaccine development against different viruses such as SARS-CoV-2, Zika, dengue and hepatitis C with options for industry collaborations. We also have clinical/immunology projects in areas of HIV and COVID-19. .