Kathryn L. Wofford

Parkinson’s disease (PD) affects 1–2% of people over 65, causing significant morbidity across a progressive disease course. The classic PD motor deficits are caused by the degeneration of dopaminergic neurons in the substantia nigra pars compacta (SNpc), resulting in the loss of their long-distance axonal projections that modulate striatal output. While contemporary treatments temporarily alleviate symptoms of this disconnection, there is no approach able to replace the nigrostriatal pathway. We applied microtissue engineering techniques to create a living, implantable tissue-engineered nigrostriatal pathway (TE-NSP) that mimics the architecture and function of the native pathway. TE-NSPs comprise a discrete population of dopaminergic neurons extending long, bundled axonal tracts within the lumen of hydrogel micro-columns. Neurons were isolated from the ventral mesencephalon of transgenic rats selectively expressing the green fluorescent protein in dopaminergic neurons with subsequent fluorescent-activated cell sorting to enrich a population to 60% purity. The lumen extracellular matrix and growth factors were varied to optimize cytoarchitecture and neurite length, while immunocytochemistry and fast-scan cyclic voltammetry (FSCV) revealed that TE-NSP axons released dopamine and integrated with striatal neurons in vitro. Finally, TE-NSPs were implanted to span the nigrostriatal pathway in a rat PD model with a unilateral 6-hydroxydopamine SNpc lesion. Immunohistochemistry and FSCV established that transplanted TE-NSPs survived, maintained their axonal tract projections, extended dopaminergic neurites into host tissue, and released dopamine in the striatum. This work showed proof of concept that TE-NSPs can reconstruct the nigrostriatal pathway, providing motivation for future studies evaluating potential functional benefits and long-term durability of this strategy. This pathway reconstruction strategy may ultimately replace lost neuroarchitecture and alleviate the cause of motor symptoms for PD patients.

Head impact sensors measure head kinematics in sports, and sensor accuracy is crucial for investigating the potential link between repetitive head loading and clinical outcomes. Many validation studies mount sensors to human head surrogates and compare kinematic measures during loading from a linear impactor. These studies are often unable to distinguish intrinsic instrumentation limitations from variability caused by sensor coupling. The aim of the current study was to evaluate intrinsic sensor error in angular velocity in the absence of coupling error for a common head impact sensor. Two Triax SIM-G sensors were rigidly attached to a preclinical rotational injury device and subjected to rotational events to assess sensor reproducibility and accuracy. Peak angular velocities between the SIM-G sensors paired for each test were correlated (R2 > 0.99, y = 1.00x, p < 0.001). SIM-G peak angular velocity correlated with the reference (R2 = 0.96, y = 0.82x, p < 0.001); however, SIM-G underestimated the magnitude by 15.0% ± 1.7% (p < 0.001). SIM-G angular velocity rise time (5% to 100% of peak) correlated with the reference (R2 = 0.97, y = 1.06x, p < 0.001) but exhibited a slower fall time (100% to 5% of peak) by 9.0 ± 3.7 ms (p < 0.001). Assessing sensor performance when rigidly coupled is a crucial first step to interpret on-field SIM-G rotational kinematic data. Further testing in increasing biofidelic conditions is needed to fully characterize error from other sources, such as coupling.