Traumatic brain injury (TBI), a neurological condition that negatively affects neural capabilities, occurs when a blunt trauma impacts the head. Following the initial injury that immediately impacts neural cell function and survival, a series of secondary injury events lead to substantial sustained inflammation for weeks to years post-injury. To develop TBI treatments that may stimulate regenerative processes, a novel drug delivery system that efficiently delivers the appropriate drug/payload to injured tissue is crucial. Hyaluronic acid (HA) hydrogels are attractive when developing a biomaterial for tissue reparation and regeneration. HA is a natural polymer with physicochemical properties that can be tuned to match the properties of the extracellular matrix (ECM) of the many tissues including the central nervous system (CNS). Here, the project objective was to develop a HA hydrogel system for local delivery of a biological payload; this objective was completed by employing a composite system with two parts. The first part is an injectable, shear-thinning bulk hydrogel, and the second is microgels for loading biological payloads. The bulk hydrogel was composed of cyclodextrin modified HA (Cd-HA) and adamantane modified HA (Ad-HA) that give rise to guest-host interactions that facilitate physical crosslinking. The microgel, composed of norbornene-HA (Nor-HA) and sulfated-HA, crosslink via chemical crosslinks upon activation of a UV photoinitiator. The sulfated-HA microgels facilitate loading of biological payloads by mimicking heparin binding sites via the conjugated sulfated group. Neuregulin I, an epidermal growth factor with neuroprotective properties, is one such protein with a heparin binding domain that may be retained in the sulfated-HA microgels. Specifically, the project focused on mechanical testing of this composite microgel/hydrogel system and also developing protein affinity assays.

Following a study conducted in 1991 supporting that kinesthetic information affects visual processing information when moving an arm in extrapersonal space, this research aims to suggest utilizing virtual-reality (VR) technology will lead to more accurate and faster data acquisition (Helms Tillery, et al.) [1]. The previous methods for conducting such research used ultrasonic systems of ultrasound emitters and microphones to track distance from the speed of sound. This method made the experimentation process long and spatial data difficult to synthesize. The purpose of this paper is to show the progress I have made in the efforts to capture spatial data using VR technology to enhance the previous research that has been done in the field of neuroscience. The experimental setup was completed using the Oculus Quest 2 VR headset and included hand controllers. The experiment simulation was created using Unity game engine to build a 3D VR world which can be used interactively with the Oculus. The result of this simulation allows the user to interact with a ball in the VR environment without seeing the body of the user. The VR simulation is able to be used in combination with real-time motion capture cameras to capture live spatial data of the user during trials, though spatial data from the VR environment has not been able to be collected.

Alginate microspheres have recently become increasingly popular in the realm of drug delivery for their biocompatibility, nontoxicity, inexpensiveness, among other factors. Recent strict regulations on microsphere size have drastically increased manufacturing cost and waste, even though the effect of size variance on drug delivery and subsequent performance is unclear. If sphere size variance does not significantly affect drug release profiles, it is possible that future ordinances may loosen tolerances in manufacturing to limit waste produced and expenditures. We use a mathematical model developed by Nickel et al. [12], to theoretically predict drug delivery profiles based on sphere size, and correlate the expected release with experimental data. This model considers diffusion as the key component for drug delivery, which is defined by Fick’s Laws of Diffusion. Alginate, chosen for its simple fabrication method and biocompatibility, was formed into microspheres with a modified extrusion technique and characterized by size. Size variance was introduced in batches and delivery patterns were compared to control groups of identical size. Release patterns for brilliant blue dye, the mock drug chosen, were examined for both groups via UV spectrometry. The absorbance values were then converted to concentration value using a calibration curve done prior to experimentation. The concentration values were then converted to mass values. These values then produced curves representing the mass of the drug released over time. Although the control and experimental values were statistically significantly different, the curves were rather similar to each other. However, when compared to the predicted release pattern, the curves were not the same. Unexpected degradation caused this dissimilarity between the curves. The predictive model was then adjusted to account for degradation by changing the diffusion coefficient in the code to a reciprocal first order exponent. The similarity between the control and experimental curves can insinuate the notion that size tolerances for microsphere production can be somewhat lenient, as a batch containing fifteen beads of the same size and one with three different sizes yields similar release patterns.