Recombinant Adeno-Associated Virus-Mediated Gene Therapy for Treatment of Familial Hypercholesterolemia in Rabbits

Familial hypercholesterolemia (FH) is a genetic disorder characterized by abnormally high concentrations of low-density lipoprotein-cholesterol (LDLcholesterol) in the blood that can contribute to heart disease. FH can result from a defect in the gene for the LDL receptor (LDL-R). FH patients lacking functional LDL-R may benefit from viral-mediated transfer of a functional copy of the open reading frame (ORF) of the LDL-R. Since a recombinant adeno-associated virus (rAAV) is not immunogenic and can be mass-produced, it shows promise for gene therapy applications. AAV6 and AAV8 have been shown to specifically transduce hepatocytes in several species, which normally remove the majority of LDL-cholesterol from the blood via LDL-R-mediated endocytosis. Because of the potential of rAAV to treat FH by delivery of a correct LDL-R ORF to hepatocytes, the liver specificity of these two AAV serotypes was evaluated. Additionally, rabbits were chosen as the animal model for this study because a specific strain of rabbits, Watanabe heritable hyperlipidemic (WHHL), adequately mimics the pathology of FH in humans. Exposure of rabbit liver to rAAV with the marker LacZ and subsequent inspection of liver tissue showed that AAV8 transduced rabbit liver more efficiently than AAV6. To assess the feasibility of producing a rAAV capable of transferring the LDL-R ORF to rabbit hepatocytes in vivo, rAAV8-LDL-R was mass-produced by a baculovirus system in suspension grown insect cells.

Developing Quantitative Methodologies for the Digital Humanities: A Case Study of 20th Century American Commentary on Russian Literature

Using scientific methods in the humanities is at the forefront of objective literary analysis. However, processing big data is particularly complex when the subject matter is qualitative rather than numerical. Large volumes of text require specialized tools to produce quantifiable data from ideas and sentiments. Our team researched the extent to which tools such as Weka and MALLET can test hypotheses about qualitative information. We examined the claim that literary commentary exists within political environments and used US periodical articles concerning Russian literature in the early twentieth century as a case study. These tools generated useful quantitative data that allowed us to run stepwise binary logistic regressions. These statistical tests allowed for time series experiments using sea change and emergency models of history, as well as classification experiments with regard to author characteristics, social issues, and sentiment expressed. Both types of experiments supported our claim with varying degrees, but more importantly served as a definitive demonstration that digitally enhanced quantitative forms of analysis can apply to qualitative data. Our findings set the foundation for further experiments in the emerging field of digital humanities.