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Experiencing trauma may adversely impact a child’s education, and research in this field requires a deeper understanding about how those working in the education system, specifically pre-service teachers, can respond and support children impacted by trauma. Pre-service teachers, who are our future teachers, play a role in recognising and helping children when signs of trauma are revealed, but risk re-traumatising children if not adequately trained during their university education.
Mothers with asthma or atopy have a higher likelihood of having autistic children, with maternal immune activation in pregnancy implicated as a mechanism. This study aimed to determine, in a prospective cohort of mothers with asthma and their infants, whether inflammatory gene expression in pregnancy is associated with likelihood of future autism.
Parent-infant interactions provide the foundation for the development of infant socioemotional wellbeing. Preterm birth can have a substantial, and often detrimental, impact on the quality of early parent-infant interactions. Sensory processing difficulties, common in preterm infants, are further associated with poorer interaction quality.
ORIGINS sub-projects are investigating the best way to provide support to new parents and positively influence the health and development of their children.
Cancers in children are very different to cancers in adults. However, most therapeutic strategies are designed explicitly for adult cancers, and then used in children if proven safe.
The Ear and Hearing Health team's vision is all children start primary school with good hearing.
An adapted novel flow cytometry methodology to delineate types of cell death in airway epithelial cells Cystic fibrosis (CF) lung disease is
Senior Research Officer
Machine learning (ML) algorithms are powerful tools that are increasingly being used for sepsis biomarker discovery in RNA-Seq data. RNA-Seq datasets contain multiple sources and types of noise (operator, technical and non-systematic) that may bias ML classification. Normalisation and independent gene filtering approaches described in RNA-Seq workflows account for some of this variability and are typically only targeted at differential expression analysis rather than ML applications.
Indigenous Australians are known to have a higher prevalence of coronary artery disease (CAD) than non-Indigenous counterparts. Atherogenic lipid profiles, characterised by low serum levels of high-density lipoprotein (HDL) and higher serum triglycerides, have been shown to be more prevalent in Indigenous Australians. The use of computed tomography coronary angiography (CTCA) for risk stratification and diagnosis of CAD has been validated in moderate risk populations, but limited data exists in specific high-risk populations such as Indigenous Australians.