Post-acute COVID-19 neuropsychiatric symptoms are not associated with ongoing nervous system injury

A proportion of patients infected with severe acute respiratory syndrome coronavirus 2 experience a range of neuropsychiatric symptoms months after infection, including cognitive deficits, depression and anxiety. The mechanisms underpinning such symptoms remain elusive. Recent research has demonstrated that nervous system injury can occur during COVID-19. Whether ongoing neural injury in the months after COVID-19 accounts for the ongoing or emergent neuropsychiatric symptoms is unclear. Within a large prospective cohort study of adult survivors who were hospitalized for severe acute respiratory syndrome coronavirus 2 infection, we analysed plasma markers of nervous system injury and astrocytic activation, measured 6 months post-infection: neurofilament light, glial fibrillary acidic protein and total tau protein. We assessed whether these markers were associated with the severity of the acute COVID-19 illness and with post-acute neuropsychiatric symptoms (as measured by the Patient Health Questionnaire for depression, the General Anxiety Disorder assessment for anxiety, the Montreal Cognitive Assessment for objective cognitive deficit and the cognitive items of the Patient Symptom Questionnaire for subjective cognitive deficit) at 6 months and 1 year post-hospital discharge from COVID-19. No robust associations were found between markers of nervous system injury and severity of acute COVID-19 (except for an association of small effect size between duration of admission and neurofilament light) nor with post-acute neuropsychiatric symptoms. These results suggest that ongoing neuropsychiatric symptoms are not due to ongoing neural injury

Immersive intelligence genomic data visualisation

Genomics data are very complex and could contain crucial information about a disease or how a treatment method may perform well on one but not on another. Understanding such genomic data would enable better insight into the correlation between genes and diseases, which could facilitate personalised treatments for the patients. Although visualisations have been increasingly used in the genomic analysis, there is still limited research work on interactive visualisations on immersive platforms, such as in Augmented and Virtual Reality. This paper presents a new interactive visualisation and navigation of genomics data in such environments. We provide an overview of the patient cohort in 3D genetic similarity-space as well as the views of the genes of interests for detail study. The visualisation employs avatars to represent the patients to enhance the realistic look-and-feel of the patients in the immersive environments. We illustrate the effectiveness of our platform through a childhood cancer dataset, B-cell Acute Lymphoblastic Leukaemia