DOI: https://doi.org/10.15368/theses.2013.190
Available at: https://digitalcommons.calpoly.edu/theses/1107
Date of Award
12-2013
Degree Name
MS in Biomedical Engineering
Advisor
Lily Laiho
Abstract
Traumatic brain injuries (TBIs) contribute to approximately 30.5% of all injury related deaths in the United States per year and approximately 1.7 million TBIs per year occur as an isolated injury or other injury. Military personnel are exposed to TBIs and have less availability to resources traditionally used to diagnose a TBI. Reactive oxygen species (ROS) play a large role in secondary traumatic brain damage, especially lipid peroxidation, following TBIs. One of the principle and most studied byproducts of lipid peroxidation is malondialdehyde (MDA). The focus of this paper was to create an initial proof-of-concept field diagnostic device to detect ROS, or constituents, following a TBI. The device was divided into three main sections: blood separation, sample separation, and detection. This thesis report examined the blood and sample separation sections of the device; however the blood separation was not developed due to university restrictions. Pre-fabricated microfluidic chips and a confocal microscope were used for the separation. Pressure was first used to drive the fluid through the channel to observe functionality of the chip with 10 um microspheres and then a MDA solution once the spheres were successful. When fluid successfully flowed through the channels with pressure, voltage was then applied to the channels to create a capillary electrophoresis (CE) system. The CE system was tested with the spheres first and then the MDA solution upon successful demonstration of voltage-driven flow. Analysis of the images was performed using ImageJ software in attempt to determine the velocity of the spheres and MDA. The results of the system appeared to successfully drive the MDA with voltage-driven flow after waiting for the residual effects of the applied pressure to reduce. However, any conclusions require more experimental data.