Filtering by
- All Subjects: Immunology
- Creators: School of Life Sciences
- Member of: Barrett, The Honors College Thesis/Creative Project Collection
- Resource Type: Text
- Status: Published
PKR interaction mapped to a region within the dsRNA-binding domain of E3 and overlapped with sequences in the C-terminus of this domain that are necessary for binding to dsRNA. Point mutants of E3 were generated and screened for PKR inhibition and direct interaction. Analysis of these mutants demonstrates that dsRNA-binding but not PKR interaction plays a critical role in the broad host range of VACV. Nonetheless, full inhibition of PKR in cells in culture requires both dsRNA-binding and PKR interaction. Because E3 is highly conserved among orthopoxviruses, understanding the mechanisms that E3 uses to inhibit PKR can give insight into host range pathogenesis of dsRNA producing viruses.
Moraxella catarrhalis is a gram negative commensal bacteria that is a primary cause of otitis media in infants and severe exacerbations of COPD in adults. M. catarrhalis treatment has become increasingly difficult and expensive over the past half-century due to the emergence of beta-lactamase producing strains. There are currently no vaccines available to protect against infections. In this paper, we propose a transcriptomics-based approach for identifying potential vaccine targets. Additionally, a novel method was used to create bacterial vaccine polypeptides composed of sequence conserved peptides secreted through the outer membrane. Polypeptides were tested for immunogenicity and protective capacity in mice. We show that relative abundance of outer membrane proteins does not correlate with immunogenicity. We also show promising results for polypeptide protection in a mouse pulmonary clearance model.
We attempted to apply a novel approach to stock market predictions. The Logistic Regression machine learning algorithm (Joseph Berkson) was applied to analyze news article headlines as represented by a bag-of-words (tri-gram and single-gram) representation in an attempt to predict the trends of stock prices based on the Dow Jones Industrial Average. The results showed that a tri-gram bag led to a 49% trend accuracy, a 1% increase when compared to the single-gram representation’s accuracy of 48%.