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    •   MOspace Home
    • University of Missouri-Columbia
    • Graduate School - MU Theses and Dissertations (MU)
    • Theses and Dissertations (MU)
    • Dissertations (MU)
    • 2020 Dissertations (MU)
    • 2020 MU dissertations - Freely available online
    • View Item
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    Development of translational models for intervertebral disc degeneration using a comparative approach for canine and human patients

    Lee, Naomi Nayoung
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    [PDF] LeeNaomi.pdf (4.168Mb)
    Date
    2020
    Format
    Thesis
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    Abstract
    Intervertebral discs (IVDs) are unique musculoskeletal tissues within functional spinal unit organs comprising the spinal column that distribute loads and allow complex movements for vertebrates. IVD degeneration has been closely associated with manifestations of symptomatic IVD disease (IVDD). IVDD spontaneously occurs in canine and human populations. As such, dogs can serve as highly relevant and ethical preclinical models for both human and canine IVDD. Chondrodystrophic (CD) and non-chondrodystrophic (NCD) breeds of dogs show different phenotypes of IVDD, each of which mimic phenotypes described for human patients. The main goal for this PhD research was to develop and validate canine models for human IVDD with a focus on distinguishing molecular characteristics of key disease phenotypes. Using biomarkers associated with inflammation and degradation, IVD health and disease were characterized for the two species. Taken together, this body of work suggests that CD and NCD dogs demonstrate distinctly different biomarker profiles in both health and disease that represent key human IVDD phenotypes such that they can be used as effective models for translational research towards clinical diagnosis, prevention, and treatment strategies for canine and human degenerative disc disorders.
    URI
    https://hdl.handle.net/10355/88894
    Degree
    Ph. D.
    Thesis Department
    Pathology and anatomical sciences (MU)
    Collections
    • Pathology and Anatomical Sciences electronic theses and dissertations (MU)
    • 2020 MU dissertations - Freely available online

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