Brain Connectivity Imaging Markers To Confirm Diagnosis For Bipolar Vs. Unipolar Depression – A Connectome Approach.
Funder
National Health and Medical Research Council
Funding Amount
$434,369.00
Summary
Differentiating Bipolar disorders from Unipolar Depression is a major clinical challenge. This misdiagnosis hinders optimal clinical care and has many deleterious consequences such self-harm, increased chances of suicide, poor prognosis, and greater health care costs related to this disorder. This project will provide urgently-needed advance in accurate identification of Bipolar disorders using Magnetic Resonance Imaging and remove one of the key obstacles to accurate diagnosis.
Sudden Cardiac Arrest: Improving Detection Of Patients At Risk
Funder
National Health and Medical Research Council
Funding Amount
$838,845.00
Summary
Sudden cardiac death accounts for ~10% of deaths in our community. Many of these deaths occur in people who could otherwise have had many more years of productive life ahead of them. The aim of our research is to determine the underlying mechanisms so that we can develop better tools for detecting underlying problems before they become life threatening and potentially develop new treatments to modify the underlying causes.
Developmental Schizotypy In The General Population: Early Risk Factors And Predictive Utility.
Funder
National Health and Medical Research Council
Funding Amount
$830,952.00
Summary
This study will determine early childhood risk factors for psychosis-proneness in children aged 11 years, and emerging signs and symptoms of mental health disorders of these children, using population data from the NSW Child Development Study. Determining risk for psychosis as early as possible in the life course will enable the provision of preventative interventions to children at critical points in development.
A Multi-national Trial To Predict Treatment Response In Subtypes Of Depression
Funder
National Health and Medical Research Council
Funding Amount
$387,489.00
Summary
Treatment of MDD using trial and error can have serious consequences. It can prolong the patient’s suffering (depression is associated with substantial morbidity, and mortality), prolong their absence from work and other productive activity and increase the burden on their family-carers. This multi-national study will collect genetics, brain function and behavioural data from a large number of participants, allowing for sensitive predictors of response to be determined.
The Biology Of Risk For Bipolar Disorder: Genetic Effects In A High-risk Longitudinal Study
Funder
National Health and Medical Research Council
Funding Amount
$856,412.00
Summary
Bipolar disorder is a severe mood disorder affecting over 350,000 Australians. Some children of bipolar disorder patients will also become ill, although currently we have no tools to predict which of these genetically at-risk young individuals will eventually develop symptoms. This study will use genetic information plus brain structural changes to predict which at-risk individuals are likely to become ill. This study will help elucidate early clinical and biological markers of bipolar disorder.
Improved seasonal rainfall prediction for grain growers using farm level data and novel modelling. Successful grain production, a key export commodity for Australia, depends heavily on reliable seasonal forecasts. However, the highly variable climate means that for Australia’s 25,000 grain growers current forecasts lack detail in space and time. Using a combination of fuzzy classification and artificial neural networks, this project will develop a locally detailed continuously updating data-driv ....Improved seasonal rainfall prediction for grain growers using farm level data and novel modelling. Successful grain production, a key export commodity for Australia, depends heavily on reliable seasonal forecasts. However, the highly variable climate means that for Australia’s 25,000 grain growers current forecasts lack detail in space and time. Using a combination of fuzzy classification and artificial neural networks, this project will develop a locally detailed continuously updating data-driven seasonal forecast system using high density climate data from the 17,000 Grain Growers Association members and climate drivers such as sea surface temperature from the Bureau of Meteorology. After validation against observed data, the forecasts will be delivered via a web-based portal to users.Read moreRead less
The Effects Of Estrogen-Responsive B Box Protein On Retinoid Sensitivity In Cancer And Its Significance In Development
Funder
National Health and Medical Research Council
Funding Amount
$82,421.00
Summary
Although effective, many cancer drugs often lead to side effects, especially in children. New therapies are needed that specifically target cancer cells while leaving normal cells unaffected. I am studying a novel protein (EBBP) which I believe has an important role in cancer cell growth. By studying EBBP I aim to be able to increase the effectiveness of the low toxic chemotherapy retinoic acid without increased side effects, as well as understand the functional role of EBBP in cancer cells.
Single-cell Optical Window Imaging In CDK1-FRET Biosensor Mice To Assess Tissue Stiffness And Optimise Delivery And Therapeutic Response To Gemcitabine/Abraxane In Pancreatic Cancer.
Funder
National Health and Medical Research Council
Funding Amount
$676,979.00
Summary
Inefficient drug response in solid tumour tissue is commonly a limiting factor in the clinical effectiveness of cancer therapies. Using cutting-edge imaging technology and 3D models that mimic the disease, we have mapped areas of poor drug response within distinct regions of tumours. Here, we pinpoint and specifically target key factors limiting efficient drug targeting in order to improve the encouraging anti-cancer profile of the new drug combination Gemcitabine/Abraxane in pancreatic cancer.
Biosensor Imaging In Preclinical Pancreatic Cancer Targeting: Taking Cancer Targeting To New Dimensions.
Funder
National Health and Medical Research Council
Funding Amount
$640,210.00
Summary
Using cutting-edge imaging technology and 3D models that mimic cancer, we can map areas of poor drug response within distinct 'stages' or regions of tumours. Here, we pinpoint and specifically target key factors limiting efficient drug response in order to improve the encouraging anti-cancer profile of new or current drugs in pancreatic cancer.