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Novel in vitro methods to understand the mechanical behavior and biological implications of fluid shear from CED devices in the brain
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Kodamasimham, Swetha. Novel in vitro methods to understand the mechanical behavior and biological implications of fluid shear from CED devices in the brain. Retrieved from https://doi.org/doi:10.7282/t3-ynj7-1p61

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TitleNovel in vitro methods to understand the mechanical behavior and biological implications of fluid shear from CED devices in the brain
NameKodamasimham, Swetha (author); Sy, Jay C. (chair); Cai, Li (internal member); Labazzo, Kristen (internal member); Rutgers University; School of Graduate Studies
Date Created2018
Other Date2018-10 (degree)
SubjectBiomedical Engineering, Convection enhanced delivery, Drug delivery devices
Extent1 online resource (61 pages) : illustrations
DescriptionConvection enhanced delivery (CED) devices are a promising therapeutic strategy to overcome some of the obstacles involved in delivering drugs to the brain. CED devices bypass the blood-brain barrier (BBB), targeting drugs locally into the interstitial spaces using pressure-mediated flow, which can increase drug penetration and efficacy compared to systemic delivery. A critical step in developing brain implants is to investigate how the mechanisms of the device effect the surrounding environment. This can provide insight into any mechanical or biological limitations of the device that need to be considered for implementation into a clinical setting. Although mechanical characterization and inflammation studies have been conducted for other kinds of brain implants, limited work has focused on applying these type of studies to the operation of CED devices specifically. As a result, how pressure-driven flow from CED devices affects local brain tissue is not yet clearly understood. This study implements unique computational and biological techniques to characterize in vitro the effects of fluid shear on local deformation and inflammation of brain tissue through both quantitative and spatial analysis. Particle image velocimetry (PIV) is an optical method designed for flow visualization that we translate to the study of fluid shear from CED devices using agarose brain phantoms as a mechanical model of brain tissue. PIV analysis was successfully able to quantify magnitudes of deformation as a function of distance and time and generate heat maps highlighting areas of most impact from fluid shear in detail that has not been done in the past. This characterization allows for predictions of how mechanical behavior from CED devices can potentially impact biological response. Infusion experiments were also conducted in 3D C8-B4 microglial cultures embedded in Matrigel that can serve as a simple model of the brain parenchyma and evaluated for elevations in tumor necrosis factor alpha (TNF-α) as the candidate inflammatory marker. However, given the small volume of affected cells relative to total cell-gel construct, this bulk quantification method proved ineffective in detecting any overall increased levels of TNF-α compared to positive (lipopolysaccharide (LPS)-treated) and negative (untreated) controls, suggesting that a spatial visualization of inflammation may be a more suitable approach for more local resolution of any biological effects from fluid shear. Using a secretory inhibitor, Brefeldin A (BFA), we develop and optimize a method to retain TNF-α within the cells for cytochemical staining to conduct spatial analysis of cell activation. With this, we accomplish the first step in developing an immunofluorescence technique can be used with the cell model to gain an understanding of spatial resolution of inflammation from fluid shear to eventually correlate with the tissue mechanics studies. Ultimately, these techniques can provide new and better tools for CED device characterization prior to in vivo studies.
NoteM.S.
NoteIncludes bibliographical references
Noteby Swetha Kodamasimham
Genretheses, ETD graduate
Persistent URLhttps://doi.org/doi:10.7282/t3-ynj7-1p61
Languageeng
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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