Here’s a batch of fresh news and announcements from across Imperial.
From a study into the risks of smokers developing more severe forms of COVID-19, to a new method for automatically detecting the ‘fingerprint’ of soundscapes, here is some quick-read news from across the College.
Smokers more at risk?
Smokers hospitalised with COVID-19 may be more likely to progress to more severe forms of the disease, including admission to intensive care.
In a review of eight published studies, a team from Imperial’s School of Public Health and Chelsea Westminster Hospital looked at the association between smoking and health outcomes.
Currently, smokers are not designated a ‘high risk’ group in the UK, but the analysis of COVID patients revealed a far higher degree of smokers progressing to serious disease compared to non-smokers (30% vs 18%).
The researchers say their analysis provides further evidence to support the WHO’s position that smokers are ‘at higher risk of developing severe disease and death’, adding that the habit may be one of the few easily modifiable risk factors for the disease.
The findings are published in the journal Smoking Induced Diseases.
Imperial’s Graduate School has announced the 2020 winners of the 4Cs Science Writing Competition:
- People's Choice Award: Clavance Lim, Department of Computing - Translating Words to Numbers
- First place: Michelle Lin, Department of Life Sciences - Cryptococcosis: The Silent Killer
- Second place: David Ho, Department of Physics - A really strong magnet can dissolve Everything
- Joint third place:
Long-term health impacts
Researchers from across the UK have begun a major study into the long-term health impacts of COVID-19.
Launched this week, the PHOSP-COVID study study will recruit 10,000 patients who have been discharged from hospital after having COVID-19, with clinical follow ups for 12 months or longer.
The study aims to determine the short to long terms health issues of people who have been hospitalised with COVID-19, relating it to geography, demographics, lifestyle and other factors.
According to the researchers, the findings should help us to understand better which medicines and care pathways were most beneficial to particular patients.
The £8.4m project funded by the NIHR and UKRI is led by University of Leicester and includes a number of researchers from Imperial’s NHLI.
Alongside his work teaching academic literacy at Imperial’s Centre for Academic English, Neil Taylor has also been working on his first novel.
Neil said: “The novel is a bittersweet comedy - a coming of age story (for both a person and a decade) set in the Yorkshire countryside in the summer of 1962. I like to think of it as the lovechild of James Herriot and Sue Townsend with a good dollop of fairy tale and a dash of magical realism. It’s basically a warm, sad, funny story about growing up and being lost then found."
Dr Mark Chadwick from Imperial’s Department of Chemistry has been awarded a prestigious Leverhulme Trust Research Project grant of £140,000 to support his work on creating chiral molecules. Chiral molecules come in either right- or left-handed versions, termed ‘chirality’, but when used as drugs, usually only one version will have any effect. Making molecules of the right chirality can prove tricky as mixes of the two are often produced, so Dr Chadwick will research new designs for catalysts used in these reactions to induce chirality.
The Trust’s Research Project Grants are awarded to researchers to undertake an innovative and original research project. The funds provide research staff costs for those working directly on the research project and associated research costs.
Researchers from Imperial have invented a method for automatically detecting the ‘fingerprint’ of soundscapes, allowing automatic detection of long-term changes and sudden anomalies.
They originally developed the method for ecological monitoring, placing sound recording devices across a partially deforested landscape, but also demonstrated that the same audio processing techniques can be used to monitor a wide range of different ecological soundscapes. They suggest this same approach could now be expanded to monitor sounds to automatically detect problems such as in water pipe networks or machinery.
The technique uses machine learning to identify features of the soundscape that are ‘normal’, such as patterns of amplitude, alerting the user to any sudden changes – such as chainsaws in a forest that shouldn’t be logged – and allowing monitoring of long-term changes.
Read the full paper in PNAS: Characterizing soundscapes across diverse ecosystems using a universal acoustic feature set
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