With the pandemic over according to public opinion — despite the rise in Australian cases thanks to the new omicron variant JN1 which touched down in October last year — COVID innovations have largely been relegated to the back pages of the news.
Yet exciting Australian breakthroughs are still taking place, with University of Queensland researchers using machine-learning to help predict the risk of secondary bacterial infections in people who have been hospitalised, and detecting whether antibiotics would the right treatment for them.
Associate Professor Kirsty Short from the School of Chemistry and Molecular Biosciences said that while it was ‘theoretically possible just to treat all COVID patients with antibiotics’ to reduce secondary bacterial infections, the potential benefit was outweighed by the risk of antimicrobial resistance.
“Estimates of the incidents of secondary bacterial infections in COVID patients are broad but in some studies 100% of fatal cases have suffered a bacterial co-infection,” Dr Short said.
“However, there’s a danger that over-treating with antibiotics could potentially lead to antibiotic resistance and the creation of bacterial superbugs. As such, we’ve helped develop a robust predictive model to determine the risk of bacterial infections in COVID patients, facilitating a careful use of antibiotics.”
The new technique is known as the ‘least absolute shrinkage and selection operator’ – or LASSO for short – and was based on the team’s discovery that the expression of just seven genes in a COVID patient could predict their risk of developing a secondary respiratory bacterial infection just 24 hours after admission.
Queensland scientists, this time from UQ and Queensland University of Technology, in collaboration with Bond University and the University of Technology Sydney, have also shed new light on the relationship between COVID and preeclampsia – which impacts some women infected with the virus during pregnancy.
The researchers found that the products of genes linked to blood pressure, preeclampsia, and inflammation were increased in the placenta of women who contracted the virus in the third trimester of their pregnancy.
“Close examination of the transcriptional alterations occurring in the placental trophoblast and villous core stroma in response to COVID infection, revealed a notable number of genes that were enriched in biological pathways previously associated with placental dysfunction,” lead author, Dr Arutha Kulasinghe from UQ’s Faculty of Medicine, said.
“Trophoblasts from the SARS-CoV-2-infected group had significantly higher levels of the enzyme nitric oxide synthase 3 (NOS3) compared to the control group,” he said.
The researchers said the data suggested that the placenta from pregnancies with SARS-CoV-2 adopted a transcriptional profile aligning with placental dysfunction that has been observed in pregnant participants who develop ‘preeclampsia-like’ syndrome.
“Our findings set the foundation for a more comprehensive understanding of placental dysfunction in pregnant individuals with COVID and offer important insights into the potential mechanisms through which SARS-CoV-2 may impact pregnancy outcomes and foetal development,” they wrote.
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