2 resultados para Acute and subcronic toxicity

em Digital Commons - Michigan Tech


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Nearly half of the US population faces the risk of developing knee osteoarthritis (OA). Both in vitro and in vivo studies can aid in a better understanding of the etiology, progression, and advancement of this debilitating disorder. The knee menisci are fibrocartilagenous structures that aid in the distribution of load, attenuation of shock, alignment and lubrication of the knee. Little is known about the biochemical and morphological changes associated with knee menisci following altered loading and traumatic impaction, and investigations are needed to further elucidate how degradation of this soft tissue advances over time. The biochemical response of porcine meniscal explants was investigated following a single bout of dynamic compression with and without the treatment of the pharmaceutical drug, anakinra (IL-1RA). Dynamic loading led to a strain-dependent response in both anabolic and catabolic gene expression of meniscal explants. By inhibiting the Interleukin-1 pathway with IL-1RA, a marked decrease in several catabolic molecules was found. From these studies, future developments in OA treatments may be developed. The implementation of an in vivo animal model contributes to the understanding of how the knee joint behaves as a whole. A novel closed-joint in vivo model that induces anterior cruciate ligament (ACL) rupture has been developed to better understand how traumatic injury leads to OA. The menisci of knees from three different groups (healthy, ACL transected, and traumatically impacted) were characterized using histomorphometry. The acute and chronic changes within the knee following traumatic impaction were investigated. The works presented in this dissertation have focused on the characterization, implementation, and development of mechanically-induced changes to the knee menisci.

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This study develops an automated analysis tool by combining total internal reflection fluorescence microscopy (TIRFM), an evanescent wave microscopic imaging technique to capture time-sequential images and the corresponding image processing Matlab code to identify movements of single individual particles. The developed code will enable us to examine two dimensional hindered tangential Brownian motion of nanoparticles with a sub-pixel resolution (nanoscale). The measured mean square displacements of nanoparticles are compared with theoretical predictions to estimate particle diameters and fluid viscosity using a nonlinear regression technique. These estimated values will be confirmed by the diameters and viscosities given by manufacturers to validate this analysis tool. Nano-particles used in these experiments are yellow-green polystyrene fluorescent nanospheres (200 nm, 500 nm and 1000 nm in diameter (nominal); 505 nm excitation and 515 nm emission wavelengths). Solutions used in this experiment are de-ionized (DI) water, 10% d-glucose and 10% glycerol. Mean square displacements obtained near the surface shows significant deviation from theoretical predictions which are attributed to DLVO forces in the region but it conforms to theoretical predictions after ~125 nm onwards. The proposed automation analysis tool will be powerfully employed in the bio-application fields needed for examination of single protein (DNA and/or vesicle) tracking, drug delivery, and cyto-toxicity unlike the traditional measurement techniques that require fixing the cells. Furthermore, this tool can be also usefully applied for the microfluidic areas of non-invasive thermometry, particle tracking velocimetry (PTV), and non-invasive viscometry.