Publications by authors named "G Stephen Dawson"

Individuals with autism spectrum disorder (ASD) tend to experience greater difficulties with social communication and sensory information processing. Of particular interest in ASD biomarker research is the study of visual attention, effectively quantified in eye tracking (ET) experiments. Eye tracking offers a powerful, safe, and feasible platform for gaining insights into attentional processes by measuring moment-by-moment gaze patterns in response to stimuli.

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Carbon dioxide geological storage is proposed as part of the solution to reach net zero emissions. The potential to mobilise heavy metals to low salinity groundwater through CO water rock geochemical reactions is a potential environmental risk factor, if CO migrates. Previous studies have focused on pure CO reactivity, however CO streams from hard to abate industries can contain gas impurities.

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Digital dermatitis (DD) poses a major animal welfare concern for the dairy industry, with even broader economic implications for the agricultural industry worldwide. The postbiotic, a fermentation product (SCFP), has had a positive influence on the innate immune system of cattle, which makes it a potential candidate as a feed supplement as part of a prevention strategy for DD. This study investigated the effect of a commercial SCFP feed supplement compared to a control feed supplement on the production of pro-inflammatory cytokines (IL-1β and IL-6) by peripheral blood mononuclear cells (PBMCs) in Holstein Friesian steers experimentally infected with DD.

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Objective: The Osteoarthritis Chronic Care Program (OACCP) has been implemented in Australian public hospitals to deliver best evidence osteoarthritis (OA) care. It is important to ensure that the OACCP continues to deliver evidence-based OA care as intended. We aimed to identify barriers and enablers to delivering the OACCP, prioritize the barriers, and generate strategies to address them.

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A concern in the field of autism electroencephalography (EEG) biomarker discovery is their lack of reproducibility. In the present study, we considered the problem of learning reproducible associations between multiple features of resting state (RS) neural activity and autism, using EEG data collected during a RS paradigm from 36 to 96 month-old children diagnosed with autism (N = 224) and neurotypical children (N = 69). Specifically, EEG spectral power and functional connectivity features were used as inputs to a regularized generalized linear model trained to predict diagnostic group (autism versus neurotypical).

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