During my Fall 2023 semester, I had the opportunity to serve as an LHSI intern in a pathology lab, where I conducted a research project on the role of p53 in sarcoma patients. The study focused on comparing primary and metastatic tumors in the lung to explore how p53 mutations might influence cancer progression and metastasis. I also registered this experience as an Honors H398 course, allowing me to engage in deeper academic reflection and enhance my research through an honors-level framework. This designation provided additional mentorship and academic rigor, further strengthening my analytical and scientific communication skills.  

The research question driving this project was: How does the expression of p53 differ between primary and metastatic sarcoma tumors in the lung, and what implications does this have for tumor behavior and treatment strategies? To address this, I developed a structured plan that included collecting and analyzing pathology slides from sarcoma patients, using immunohistochemistry to detect p53 expression. The project involved quantifying biomarker levels in both primary and metastatic tumor samples. 

For the analysis, I assembled digital pathology slides annotated with relevant clinical data, enabling a comparison of p53 expression across tumor sites. Using statistical analysis tools, I assessed patterns and variations in expression, seeking correlations between p53 levels and metastatic potential. 

The findings revealed distinct differences in p53 expression between primary and metastatic tumors, suggesting that altered p53 expression may play a role in tumor progression. These results contribute to a better understanding of molecular pathology and highlight potential avenues for targeted therapies in sarcoma treatment. 

This hands-on experience significantly enhanced my analytical and presentation skills while expanding my knowledge of cancer biology. The project solidified my aspirations in pathology and biomedical research, preparing me for future academic and professional challenges. 

During my Fall 2024 semester, I developed a research poster comparing two AI databases, Aperio and QuPath, to evaluate their effectiveness in analyzing pathology data. Building on my Fall 2023 research on p53 in sarcoma patients, specifically comparing primary and metastatic lung tumors, I sought to explore how these databases could aid in visualizing and quantifying pathology slides for biomarker studies. I also registered this experience as an Honors H398 course, allowing me to engage in a more in-depth academic analysis and refine my research through an honors-level framework. This designation provided additional mentorship and academic rigor, further strengthening my ability to critically assess and communicate scientific findings.  

The research question driving this project was: Which AI database, Aperio or QuPath, provides more reliable and efficient tools for analyzing pathology images in studies involving p53 in sarcoma patients? My methodology involved using the same dataset from my Fall 2023 project and applying it to both platforms to assess their functionality, accuracy, and ease of use. This included importing slide images, applying consistent analysis protocols, and comparing the outputs from both databases.

To address this question, I analyzed digital pathology slides annotated with p53 biomarkers. The analysis involved measuring the databases' capabilities to accurately identify and quantify biomarker expression, including parameters such as user interface design, computational efficiency, and result accuracy.

I found that while both databases were effective, they had distinct strengths. Aperio excelled in streamlined workflows for large datasets, while QuPath offered superior customization and flexibility for specific analyses. These findings suggest that the choice between these databases depends on the scale and specific requirements of the research project.

The conclusions drawn from this study emphasize the importance of selecting tools that align with the research objectives. This experience reinforced my skills in critical evaluation of research tools, data analysis, and technical problem-solving. Continuing my work in the same pathology lab since Fall 2023 has further enriched my expertise and contributed to my growth as a researcher.

During the Spring 2025 semester, I am conducting a research project analyzing the causes of death in Marion County from 2020 to 2024. This study aims to identify trends, patterns, and potential public health concerns based on mortality data over the past five years. By examining this data, I hope to gain insights into the leading causes of death in the county and assess how factors such as public health policies, socioeconomic conditions, and external influences may have contributed to these trends. I also registered this research as an Honors H398 course, allowing me to engage in a more rigorous academic analysis and deepen my understanding through an honors-level framework. This designation provides additional mentorship and academic structure, enhancing my ability to critically interpret data and communicate my findings effectively 

The central research question for this project is: What are the most common causes of death in Marion County from 2020 to 2024, and what patterns emerge when analyzing this data over time? To address this, I am gathering information directly from the Marion County Coroner's Office, which provides official death records and case data. My methodology involves categorizing the data by cause of death, demographic factors, and year to identify any significant changes or emerging trends. 

For data analysis, I am compiling statistics from coroner reports and visualizing the findings through charts and comparative models. This will allow me to highlight key trends, such as increases or decreases in certain types of deaths, and investigate potential correlations with public health events, policy changes, or broader societal factors. 

Preliminary findings from this research will be synthesized into a research poster, which will present the data in a clear and informative way. The goal of the poster is to provide valuable insights into mortality trends in Marion County, contributing to discussions on public health, forensic science, and community safety. This experience is enhancing my skills in data analysis, research interpretation, and scientific communication, further preparing me for a career in forensic pathology and biomedical research.