Brittany Coats, Ph.D. - US grants

? DESCRIPTION (provided by applicant): Retinal detachment is the separation of the photosensitive cells from the retinal pigment epithelium and occurs in approximately 35% of the population. It can lead to blindness or severe visual impairment if not treated urgently. Tractiona retinal detachment affects both children and adults, and is caused by the vitreous of the eye pulling on the retina in regions of strong adhesion at the vitreoretinal interface. Several qualitative studies on the structural and protein composition of this interface suggest that collagen plays an important role in adhesion. Other studies hypothesize that abundant glycoproteins at the vitreoretinal interface, such as fibronectin and laminin, contribute to vitreoretinal adhesion. Despite the advancement in understanding the presence and structure of proteins at the vitreoretinal interface, there has been no direct measurement of vitreoretinal adhesion or quantification of the contribution of these proteins to adhesive forces. This paucity of data hinders the development of numerical models for investigating retinal detachment in children and adults. The objectives of this proposal are to measure region- and age-specific vitreoretinal adhesion and quantify the contribution of collagen and glycoproteins to the measured adhesive properties. To achieve these objectives, we propose to capitalize on a novel custom-made device created to perform adhesion peel tests on the retina without dissection or unintentional disruption of the vitreoretinal interface. Adhesion will be measured in three regions of the eye (anterior, posterior and equator) and in two ages (newborn and adult). Then, we propose to manipulate the concentration and structural integrity of collagen, laminin and firbronectin to determine how removal of these proteins affects measurements of vitreoretinal adhesion. Quantification of protein density before and after manipulation will be determined through transmission electron microscopy and immunohistochemistry. The proposed studies will be the first biomechanical investigation into the adhesive properties of the vitreoretinal interfac and will provide data to develop numerical tools for predicting retinal detachment in children and adults. Furthermore, evaluation of regional mechanisms of adhesion with age can spur novel strategies for prevention and treatment of retinal detachment that is less invasive than the current standard of care.

Traumatic brain injury is a leading cause of death and disability in the United States. Over 1.7
million people sustain a brain injury each year and make up one-third of all injuries seen in the
emergency room. Developing rehabilitation and treatment strategies to manage this disease are
important, but preventing the occurrence of brain trauma is also critical component to the solution.
The goal of this proposal is to reduce the risk of traumatic brain injury through smart technology
that collects sensory data to predict and characterize head impact in real-time, optimizes protective
mechanisms based on those impact characteristics, and sends impact trauma attributes to a clinical
database for further analysis and injury risk prediction. This technology will substantially improve
traumatic brain injury prevention and diagnosis in motor vehicle crashes, sports, and industrial
accidents. To accomplish this goal, fundamental research efforts include (1) real-time situational
monitoring to predict when and how dangerous impacts are about to occur and (2) active
prevention mechanisms to reduce the risk of brain injury impact. Initial evaluation of the
technology is in a sports setting, but the system components can be widely adaptive for
implementation in motor vehicles, industrial safety helmets, and living environments for the
elderly.
The research goals of this proposal are to (1) reduce the risk of traumatic brain injury through
advanced situational monitoring, musculoskeletal activation, and impact-specific force reduction;
and (2) to improve potential identification of head injury risk based on multiscale brain
deformation modeling. These goals are accomplished by integrating four fundamental research
efforts. First, tracking and collision detection algorithms are developed based on radio frequency
(RF) sensing, processing, and flexible antenna design. When used in conjunction with triaxial
accelerometers, gyroscopes, and magnetometers, these algorithms provide the sensing capabilities
required to detect objects, capture directional velocity data of surrounding objects, and process
data in real-time to determine probabilities and characteristics of impending collision. Second,
musculoskeletal clenching following auditory warning is investigated as a means of minimizing
head angular acceleration following head or body impact. The development of auditory warning
cues and muscle clench strategies utilizes kinematic musculoskeletal modeling and human subject
studies to identify required auditory cues and response times as well as muscle activation
parameters that best mitigate head angular acceleration during a collision. Third, active force
reduction specific to impending impact characteristics are implemented using a unique controllable
air-filled bladder. Optimal pressure and deflection characteristics of the bladder are based on
impact velocity and direction, and evaluated with a novel three-dimensional multiscale finite
element model of the human head. This model incorporates anatomical variability in the
microstructures at the brain-skull interface, a region that is critical to predictions of head injury.
The fourth fundamental research area uses the multiscale model to investigate the relationship of
head impact force and acceleration to regional deformation of brain tissue upon impact. These
studies will be used to improve predictions of TBI risk from impact kinematics.