Publications by authors named "Ieisha Scott"
Article Synopsis
- - The study measured protein levels in 986 individuals to predict the severity of COVID-19, using both protein data and clinical risk factors to build predictive models.
- - A baseline model using age and sex achieved a prediction accuracy of 65%, but incorporating 92 specific proteins improved this accuracy to 88% in the initial group and maintained 86% in a separate test group.
- - Findings indicate that early-stage protein measurements can effectively predict COVID-19 severity, highlighting the need for further research to integrate these measurements into clinical practice.
Article Synopsis
- This study investigates how severe COVID-19 affects levels of immune-related proteins and their differences based on sex.
- Researchers analyzed data from 580 patients by measuring 147 immune proteins during the first 14 days of infection to uncover significant differences between severe cases and controls.
- The findings revealed that 69 proteins differed significantly between groups, and some proteins showed variations between sexes, which could help explain the differing outcomes in COVID-19 severity based on gender.
Multisystem inflammatory syndrome in children (MIS-C) presents with fever, inflammation and pathology of multiple organs in individuals under 21 years of age in the weeks following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Although an autoimmune pathogenesis has been proposed, the genes, pathways and cell types causal to this new disease remain unknown. Here we perform RNA sequencing of blood from patients with MIS-C and controls to find disease-associated genes clustered in a co-expression module annotated to CD56CD57 natural killer (NK) cells and exhausted CD8 T cells.
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