Framed by others: A Technology-Based Investigation of Contexual Effects on Body Perception
This project examines how social and environmental context influences perceptions of female body size using a technology-driven experimental design. Through the use of computer-generated stimuli and digitally constructed environments, I investigated whether body size judgments are shaped by social comparison (being presented alone versus in a group) and by contextual cues associated with physical activity (gym settings) versus non-physical activity spaces (office settings).
Participants viewed standardized digital images and provided body size ratings using a continuous computer-based scale, allowing for precise, quantitative measurement of perceptual bias. Evidence of success is demonstrated through the successful design and execution of a controlled repeated-measures study, the collection of high-resolution perceptual data, and the identification of consistent contrast effects in body size perception. Preliminary findings replicated prior research by showing that individuals are not perceived differently when surrounded by similar-sized bodies but are rated as thinner or heavier when flanked by bodies of different sizes.
These findings were strong enough to support acceptance and presentation at undergraduate research conferences, validating both the rigor and relevance of the project. The integration of digital stimuli and statistical analysis tools optimized experimental control and strengthened the reliability of the results. Key lessons learned include the importance of technology in minimizing bias and increasing precision in behavioral research, as well as the complexity of perception as a socially constructed process rather than an objective judgment. This project reinforced that visual biases particularly around body size can be subtle yet systematic, mirroring the ways stigma operates in healthcare, fitness, and public spaces. As an aspiring medical professional committed to health equity and advocacy, this research informed my understanding of how implicit bias can shape patient experiences and underscored the need for inclusive, evidence-based approaches in medicine and public health.
Using gene editing technology and AI to advance scientific investigation
My research objectives are to determine the multiple mutations present in the original ypt7-38 allele using thermal self-regulation technology and diagnostic genetic approaches that incorporate temperature shifts, fluorescent dyes, and molecular readouts. In Saccharomyces cerevisiae, vesicle and membrane fusion events at endosomes and lysosomes are regulated by the Rab GTPase Ypt7, the ortholog of human Rab7, which controls the delivery of proteins and membranes for lysosomal degradation. Eukaryotic cells are defined by membrane-bound compartments known as organelles, and Rab GTPase signaling proteins function at organelle membranes to regulate fusion between transport vesicles and target compartments. When bound to GTP, Rabs are in their active state and recruit membrane tethers and fusion factors; when bound to GDP, they are inactive.
The temperature-sensitive allele ypt7-38 was generated through random mutagenesis, yet its exact nucleotide sequence has not been reported. To resolve this, genomic DNA will be extracted from candidate ypt7-38 strains and amplified using thermocycler-based gene replication technology. The resulting products will be analyzed using polar-mediated diffusion and fluorescent labeling techniques to identify sequence variations and assess their functional relevance under different temperature conditions. These experimental methods provide students with direct, hands-on experience using advanced molecular biology technologies, including thermocyclers, fluorescence-based diagnostics, and temperature-regulated genetic assays.
In parallel, AI-assisted analytical tools will be used to support data interpretation and experimental design. Machine-learning–based pattern recognition and structured journal analysis will help correlate mutation profiles with observed temperature-sensitive phenotypes and vesicle trafficking defects. These analytics-driven approaches not only enhance experimental accuracy but also enable the development of new academic initiatives by training undergraduate researchers to integrate computational analysis with wet-lab experimentation. Understanding and contextualizing prior research through AI-assisted literature analysis is essential for interpreting results and preparing students to engage critically with complex biological data. Overall, this research will advance scientific investigation by combining gene editing, thermal regulation, and AI-assisted analysis to dissect Rab-mediated membrane trafficking. Insights gained from the ypt7-38 allele will not only clarify fundamental mechanisms of vesicle fusion in yeast and human disease; in addition, to active hands-on learning with advanced technologies and the use of data analytics to shape research-driven academic development.