Publications by authors named "Rachel M Harrison"
Article Synopsis
- The study highlights the challenges in developing SMS health interventions due to lack of transparency and limited public data access, suggesting a need for a more efficient process in content creation.
- The research introduces generative AI, specifically using GPT-3.5, to create a robust dataset of 1150 messages focused on medication adherence for type 2 diabetes, ensuring they meet specific content and SMS standards.
- The findings present the largest collection of AI-generated health messages, demonstrating that a significant majority meet readability and character length requirements, while also showcasing message diversity comparable to existing datasets.
RNA interference (RNAi), a naturally occurring phenomenon in eukaryotic organisms, is an extremely valuable tool that can be utilized in the laboratory for functional genomic studies. The ability to knockdown individual genes selectively via this reverse genetic technique has allowed many researchers to rapidly uncover the biological roles of numerous genes within many organisms, by evaluation of loss-of-function phenotypes. In the major human malaria vector Anopheles gambiae, the predominant method used to reduce the function of targeted genes involves injection of double-stranded (dsRNA) into the hemocoel of the adult mosquito.
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