UMD Theses and Dissertations
Permanent URI for this collectionhttp://hdl.handle.net/1903/3
New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a given thesis/dissertation in DRUM.
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Item LEVERAGING SELF-ASSEMBLY AND BIOPHYSICAL DESIGN TO BUILD NEXT-GENERATION IMMUNOTHERAPIES(2022) Froimchuk, Yevgeniy; Jewell, Christopher M; Bioengineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The immune system has evolved mechanisms to respond not only to specific molecular signals, but also to biophysical cues. Interestingly, research at the interface of biomaterials and immunology has also revealed that the biophysical properties and form of vaccines and immunotherapies impact immunological outcomes. For example, the intermolecular distance between antigen molecules on the surface of nanoparticles can impact formation of T cell receptor clusters that are critical during T cell activation. Despite the importance of biophysical cues in tuning the immune response, the connections between these parameters and immunological outcomes are poorly understood in the context of immunotherapy. Immunotherapies harness an individual’s immune system to battle diseases such as autoimmunity. During autoimmune disease, the immune system malfunctions and mistakenly attacks self-tissue. Immunotherapies can help tailor and guide more effective responses in these settings, as evidenced by recent advances with monoclonal antibodies and adoptive cell therapies. However, despite the transformative gains of immunotherapies for patients, many therapies are not curative, work only for a small subset of patients, and lack specificity in distinguishing between healthy and diseased cells, which can cause severe side effects. To overcome these challenges, experimental strategies are attempting to co-deliver self-antigens and modulatory cues to reprogram dysfunctional responses against self-antigens without hindering normal immune function. These strategies have shown exciting potential in pre-clinical models of autoimmune disease but are unproven in clinical research. Understanding how biophysical features are linked to immunological mechanisms in these settings would add a critical dimension to designing translatable, antigen-specific immunotherapies. Self-assembling materials are a class of biomaterials that spontaneously assemble in aqueous solution. Self-assembling modalities are useful technologies to study the links between biophysical parameters and immune outcomes because they offer precise control and uniformity of the biophysical properties of assembled moieties. Our lab leveraged the benefits of self-assembly to pioneer development of “carrier-free” immunotherapies composed entirely of immune signals. The therapies are composed of self-antigens modified with cationic amino acid residues and anionic, nucleic acid based modulatory cues. These signals are self-assembled into nanostructured complexes via electrostatic interactions. The research in this dissertation utilizes this platform as a tool to understand how tuning the biophysical properties of self-antigens impacts molecular interactions during self-assembly and in turn, how changes in biophysical features are linked to immunological outcomes. Surface plasmon resonance studies revealed that the binding affinity between signals can be tuned by altering overall cationic charge and charge density of self-antigen, and by anchoring the self-antigen with arginine or lysine residues. For example, the binding affinity between signals can be increased by increasing the total cationic charge on the self-antigen, and by anchoring the self-antigen with arginine residues rather than lysine residues. Computational modeling approaches generated insights into how molecular interactions between signals, such as hydrogen bonding, salt-bridges, and hydrophobic interactions, change with different design parameters. In vitro assays revealed that a lower binding affinity between self-assembled signals was associated with greater reduction of inflammatory gene expression in dendritic cells and more differentiation of self-reactive T cells towards regulatory phenotypes that are protective during autoimmunity. Taken all together, these insights help intuit how to use biophysical design to improve modularity of the self-assembly platform to incorporate a range of antigens for distinct disease targets. This granular understanding of nanomaterial-immune interactions contributes to more rational immunotherapy design.Item MODELING POTENTIAL HABITAT OF CHESAPEAKE BAY LIVING RESOURCES(2012) Schlenger, Adam James; North, Elizabeth; Marine-Estuarine-Environmental Sciences; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)A quantitative understanding is needed to identify the impacts of climate change and eutrophication on the habitat of living resources so that effective management can be applied. A systematic literature review was conducted to obtain the physiological tolerances to temperature, salinity, and dissolved oxygen for a suite of Chesapeake Bay species. Information obtained was used to define required and optimal habitat conditions for use in a habitat volume model. Quality matrices were developed in order to quantify the level of confidence for each parameter. Simulations from a coupled oxygen and hydrodynamic model of the Chesapeake Bay were used to estimate habitat volumes of juvenile sturgeon (Acipenser oxyrinchus) and to assess sensitivity of habitat to environmental factors. Temperature and salinity define spring and fall habitat and a combination of salinity, temperature and dissolved oxygen influence habitat in summer. Both fixed criteria and bioenergetics habitat volume models yielded similar results.