Closing the data gap: High throughput screening of nanoparticle toxicity. The nanotechnology sector is experiencing an exponential growth period with over 100 products containing manufactured nanoparticles entering the market every year. Ensuring growth of the sector needs to be balanced against the imperative of protecting both human and environmental safety. This project aims to develop new methodological and conceptual avenues to close the gap between innovation in nanotechnology and risk ass ....Closing the data gap: High throughput screening of nanoparticle toxicity. The nanotechnology sector is experiencing an exponential growth period with over 100 products containing manufactured nanoparticles entering the market every year. Ensuring growth of the sector needs to be balanced against the imperative of protecting both human and environmental safety. This project aims to develop new methodological and conceptual avenues to close the gap between innovation in nanotechnology and risk assessment. This is intended to be achieved by developing and validating high-throughput in vitro toxicity screening platforms for manufactured nanoparticles. The approach is based on advanced lab-on-a-chip microfluidic technologies. The predictive power of the platform will be refined and optimised via ex-vivo and in-vivo models.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160101565
Funder
Australian Research Council
Funding Amount
$330,000.00
Summary
Flexible data modelling via skew mixture models:challenges and applications. This project seeks to explore new models for handling data with non-normal features. Parametric distributions are fundamental to statistical modelling and inference. For centuries, the ‘normal’ distribution has been the dominant model for continuous data. However, real data rarely satisfy the assumption of normality. There is thus a strong demand for more flexible distributions. This project aims to develop new methodol ....Flexible data modelling via skew mixture models:challenges and applications. This project seeks to explore new models for handling data with non-normal features. Parametric distributions are fundamental to statistical modelling and inference. For centuries, the ‘normal’ distribution has been the dominant model for continuous data. However, real data rarely satisfy the assumption of normality. There is thus a strong demand for more flexible distributions. This project aims to develop new methodologies in finite mixture modelling using skew component distributions to provide better models for handling data with non-normal features (such as skewness, heavy/light tails, and multimodality). Applications may include security intrusion detection, clinical diagnosis and prognosis, and flow and mass cytometry.Read moreRead less
Positron Nano-Dosimetry: Fundamental Measurements of Positron Interactions and their use in State-of-the-Art Modelling of Positron Transport. This proposal will provide unique experimental and theoretical information on how positrons, the electron antiparticles, interact with matter, in particular with biologically important molecules. This data will be used in a unique set of modelling approaches which will provide, for the first time, an insight into how positrons are transported through gases ....Positron Nano-Dosimetry: Fundamental Measurements of Positron Interactions and their use in State-of-the-Art Modelling of Positron Transport. This proposal will provide unique experimental and theoretical information on how positrons, the electron antiparticles, interact with matter, in particular with biologically important molecules. This data will be used in a unique set of modelling approaches which will provide, for the first time, an insight into how positrons are transported through gases, liquids and ultimately, soft matter. It will thus have important ramifications for diagnostic tools such as Positron Emission Tomography. The fundamental research will also shed light on one of the key 'mysteries' of life - why the biological building blocks of life possess a definite " handedness", or chirality.Read moreRead less
Protein biosensors for detecting smoke exposure of grapes. Bush fires and controlled burns that take place in the vicinity of vineyards can lead to grape contamination with tasteless phenolic glucosides. Their hydrolysis during wine making leads to “smoke taint” – an unpleasant medicinal taste that can render wine undrinkable. We will apply a combination of organic synthesis, protein engineering and directed evolution to develop protein-based biosensors of phenolic glucosides. These biosensors w ....Protein biosensors for detecting smoke exposure of grapes. Bush fires and controlled burns that take place in the vicinity of vineyards can lead to grape contamination with tasteless phenolic glucosides. Their hydrolysis during wine making leads to “smoke taint” – an unpleasant medicinal taste that can render wine undrinkable. We will apply a combination of organic synthesis, protein engineering and directed evolution to develop protein-based biosensors of phenolic glucosides. These biosensors will be used to devise a simple portable colorimetric test that can be performed in the vineyard or the winery. The ability to rapidly determine the level of grape contamination with phenolic glucosides would give Australian wine growers and wine makers a powerful tool to mitigate the effects of bushfires.Read moreRead less