Validation of Ultrasound Molecular Imaging Agents for Diabetic Kidney Disease via Analysis of Bio-Molecular Interactions via MATLAB Software and Microfluidics (2023)

Undergraduate: Emma Rosentreter

Faculty Advisor: Kennita Johnson
Department: Biomedical Engineering

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The invasiveness of diabetic kidney disease (DKD) allows harmful toxins to accumulate in the bloodstream due to damage to the kidneys’ filtering ability. As patients with this disease rarely display physical symptoms, the most common way to test for DKD is through markers in blood and urine. Ultrasound imaging with targeted microbubbles is a more rapid approach that may be able to evaluate disease progression through direct identification of abnormal cell clusters. The main aim of this project is to confirm that microbubbles manufactured to target vascular endothelial growth factor receptors (VEGFRs) will specifically interact with and adhere to cells that overexpress the receptor indicating cancerous growth. This semester, primary research associated with this aim culminated in the creation of a standard image processing protocol that could be utilized under both static and flow conditions to identify microbubbles in a microfluidic chamber seeded with cells and quantify their movement relative to the cells. Image processing tools were generated mainly in MATLAB to identify differences in movement between microbubbles in these chambers with and without cells seeded. Two experimental models led to the development of these tools: optical imaging of unlabeled, untagged microbubbles under static and flow conditions in microtubes, and fluorescent imaging of labeled, untagged microbubbles under static and flow conditions in microfluidic chips with cells. Future directions for this project will include tagging microbubbles to note how they target and interact with cells with abnormal receptor expression.

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