Scott, Brandon

• Ph.D., South Dakota State University

• B.S., Slippery Rock University

Project Title: Pixels to Principles: Dissecting the Mechanobiology of Phagocytosis via Event-Driven Smart Microscopy

The immune system’s ability to distinguish between eat and escape is a fundamental decision made by macrophages during phagocytosis. When macrophages encounter motile targets, such as neutrophils or cancer cells, they engage in a "mechanical tug-of-war." If the target generates sufficient counter-forces, it can physically disrupt the macrophage’s grip, allowing it to escape engulfment. Understanding the biophysical rules of this contest is critical for developing new immunotherapies, yet current microscopy methods fail to capture the decisive initial seconds of the interaction due to the difficulty of predicting exactly when and where cells will meet.

This project overcomes this barrier by developing a "Smart Microscope" platform. We combine a custom-built, high-speed Oblique Plane Microscope (OPM) with a robotic cell delivery system that places target cells directly into the microscope’s field of view with <50 µm precision. This automation allows us to deterministically capture the "time-zero" of immune contact. Once acquisition begins, real-time artificial intelligence (AI) tracks the interaction, adjusting the imaging parameters on-the-fly to capture high-resolution 3D evidence of the mechanical forces at play. Simultaneously, we are validating high-performance, web-based software to visualize and share these massive 3D datasets, democratizing access to complex imaging data.

Impact:

• Scientific: This research will generate the first quantitative maps of the forces governing immune cell decision-making, providing the pilot data necessary to secure federal funding (NSF CAREER, NIH R15).

• Educational: The project serves as a training engine for South Dakota students through a "CURE-to-VIP" pipeline. Undergraduate researchers are not just data collectors; they are the engineers who fabricate the microfluidic chips (using high-resolution resin 3D printing) and refine the robotic hardware. This hands-on approach builds a workforce skilled at the intersection of biomedical engineering, robotics, and data science.

• Infrastructure: By establishing rigorous data management and visualization benchmarks in collaboration with the Data Science Core (DSC), this project creates a validated pipeline for sharing terabyte-scale volumetric data, benefiting the broader INBRE network.