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
Bridging the gap between crop pollination services and pollinator health. Insect pollinators play an integral role in the quantity and quality of production for many food crops, yet there is growing concern that in agricultural landscapes, the limited availability of floral and non-floral resources might be contributing to global pollinator health declines. This project will synthesize global datasets, develop new methodological tools and conduct new, targeted empirical work to develop an integ ....Bridging the gap between crop pollination services and pollinator health. Insect pollinators play an integral role in the quantity and quality of production for many food crops, yet there is growing concern that in agricultural landscapes, the limited availability of floral and non-floral resources might be contributing to global pollinator health declines. This project will synthesize global datasets, develop new methodological tools and conduct new, targeted empirical work to develop an integrated approach to pollinator resource management with the explicit objectives of maintaining both wild pollinator health and to support crop pollination service delivery in modified systems.Read moreRead less