Neural electrodes are an important part of brain-machine interface devices that can restore functionality to patients with sensory and movement impairments including spinal cord injury and limb loss. Currently, chronically implanted neural electrodes induce an unfavorable tissue response which includes inflammation, scar formation, and neuronal cell death, eventually causing loss of electrode functionality in the long term. The objective of this research was to develop a coating to improve the tissue response to implanted neural electrodes. The hypothesis was that coating the surface of neural electrodes with a non-fouling, anti-inflammatory coating would cause reduced inflammation and a better tissue response to the implanted electrode. We developed a polymer coating with non-fouling characteristics, incorporated an anti-inflammatory agent, and engineered a stimulus-responsive degradable portion for on-demand release of the anti-inflammatory agent in response to inflammatory stimuli. We characterized the coating using XPS and ellipsometry, and analyzed cell adhesion, cell spreading, and cytokine release in vitro. We analyzed the in vivo tissue response using immunohistochemistry and microarray qRT-PCR. Although no differences were observed among the samples for inflammatory cell markers, lower IgG penetration into the tissue around PEG + IL-1Ra coated electrodes suggests an improvement in BBB integrity. Gene expression analysis showed higher expression of IL-6 and MMP-2 around PEG + IL-1Ra samples, as well as an increase in CNTF expression, an important marker for neuronal survival. An important finding from this research is the increased neuronal survival around coated electrodes compared to uncoated controls, which is a significant finding as neuronal survival near the implant interface is an essential part of maintaining electrode functionality.
Identifer | oai:union.ndltd.org:GATECH/oai:smartech.gatech.edu:1853/54007 |
Date | 21 September 2015 |
Creators | Gutowski, Stacie Marie |
Contributors | García, Andrés |
Publisher | Georgia Institute of Technology |
Source Sets | Georgia Tech Electronic Thesis and Dissertation Archive |
Language | en_US |
Detected Language | English |
Type | Dissertation |
Format | application/pdf |
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