ingest cdrApp 2017-07-06T12:44:26.430Z f230b17a-68de-497f-ac05-5cb17af9fe4f modifyDatastreamByValue RELS-EXT cdrApp 2017-07-06T13:18:14.090Z Setting exclusive relation modifyDatastreamByValue RELS-EXT fedoraAdmin 2017-07-06T13:32:47.490Z Setting exclusive relation modifyDatastreamByValue RELS-EXT fedoraAdmin 2017-07-06T13:32:55.705Z Setting exclusive relation addDatastream MD_TECHNICAL fedoraAdmin 2017-07-06T13:33:04.036Z Adding technical metadata derived by FITS modifyDatastreamByValue RELS-EXT fedoraAdmin 2017-07-06T13:33:20.260Z Setting exclusive relation addDatastream MD_FULL_TEXT fedoraAdmin 2017-07-06T13:33:29.747Z Adding full text metadata extracted by Apache Tika modifyDatastreamByValue RELS-EXT fedoraAdmin 2017-07-06T13:33:45.850Z Setting exclusive relation modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-01-25T10:38:07.309Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-01-27T10:55:06.469Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-03-14T07:43:05.117Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-05-17T19:19:14.942Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-07-11T06:14:07.712Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-07-18T02:27:22.919Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-08-16T15:38:37.165Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-09-27T02:08:44.484Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2018-10-12T02:38:51.582Z modifyDatastreamByValue MD_DESCRIPTIVE cdrApp 2019-03-20T21:04:26.510Z Timothy Wessler Author Department of Mathematics College of Arts and Sciences Mathematical Modeling of Biological Processes at the Cellular, Tissue, and System Levels In this work, mathematical modeling is used in conjunction with in vivo and in vitro experiments to investigate disparate biological phenomena at various scales, including cell rounding, virus trapping, and drug delivery. First, a rapid change in cell morphology from a spread to a rounded state is modeled. This transition reveals a several-fold greater cell surface than is required to enclose a perfectly round object of the same volume, and an open question is how this extra surface is stored. A Hamiltonian model, where the energy cost is minimized, is used to address this question and reproduce statistics of the surface morphology. Next, antibody attachments and detachments to pathogens moving through a biological environment are modeled. Experiments demonstrate that a pathogen with absolutely no affinity to mucus can become trapped in a mucus network in the presence of antibodies. Antibodies and mucus work cooperatively to trap pathogens by tethering the pathogen to the mucus via the antibody. Both a continuum reaction-diffusion model and a stochastic model are used to simulate the pathogen and antibody movement and binding kinetics. This work generates many important insights into the design of antibodies that use trapping to protect against foreign pathogens infecting underlying tissue. Finally, the movement of a nanoparticle drug from organ to organ throughout the body is modeled. Covalently attaching polyethylene glycol (PEG) to a drug helps maintain an adequately high concentration in the blood. However, the anti-PEG antibodies increasingly common throughout the population attach to PEG and accelerate the elimination of PEGylated drugs. A possible strategy to temporarily lower the concentration of free anti-PEG antibodies is to introduce free PEG that will bind to free anti-PEG antibodies, thus depleting their numbers before the PEGylated drug treatment begins. This work uses a compartment model with local dynamics at different scales within different compartments to model the organ-specific changes in concentrations of the PEGylated drug, the free PEG, and the anti-PEG antibodies, as well as the binding kinetics. The results lay out guidelines for a nanoparticle PEGylated drug therapy. Spring 2017 2017 Applied mathematics eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Mathematics Mark Forest Thesis advisor Samuel Lai Thesis advisor Boyce Griffith Thesis advisor David Adalsteinsson Thesis advisor Katherine Newhall Thesis advisor text Timothy Wessler Creator Department of Mathematics College of Arts and Sciences Mathematical Modeling of Biological Processes at the Cellular, Tissue, and System Levels In this work, mathematical modeling is used in conjunction with in vivo and in vitro experiments to investigate disparate biological phenomena at various scales, including cell rounding, virus trapping, and drug delivery. First, a rapid change in cell morphology from a spread to a rounded state is modeled. This transition reveals a several-fold greater cell surface than is required to enclose a perfectly round object of the same volume, and an open question is how this extra surface is stored. A Hamiltonian model, where the energy cost is minimized, is used to address this question and reproduce statistics of the surface morphology. Next, antibody attachments and detachments to pathogens moving through a biological environment are modeled. Experiments demonstrate that a pathogen with absolutely no affinity to mucus can become trapped in a mucus network in the presence of antibodies. Antibodies and mucus work cooperatively to trap pathogens by tethering the pathogen to the mucus via the antibody. Both a continuum reaction-diffusion model and a stochastic model are used to simulate the pathogen and antibody movement and binding kinetics. This work generates many important insights into the design of antibodies that use trapping to protect against foreign pathogens infecting underlying tissue. Finally, the movement of a nanoparticle drug from organ to organ throughout the body is modeled. Covalently attaching polyethylene glycol (PEG) to a drug helps maintain an adequately high concentration in the blood. However, the anti-PEG antibodies increasingly common throughout the population attach to PEG and accelerate the elimination of PEGylated drugs. A possible strategy to temporarily lower the concentration of free anti-PEG antibodies is to introduce free PEG that will bind to free anti-PEG antibodies, thus depleting their numbers before the PEGylated drug treatment begins. This work uses a compartment model with local dynamics at different scales within different compartments to model the organ-specific changes in concentrations of the PEGylated drug, the free PEG, and the anti-PEG antibodies, as well as the binding kinetics. The results lay out guidelines for a nanoparticle PEGylated drug therapy. Spring 2017 2017 Applied mathematics eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Mathematics Mark Forest Thesis advisor Samuel Lai Thesis advisor Boyce Griffith Thesis advisor David Adalsteinsson Thesis advisor Katherine Newhall Thesis advisor text Timothy Wessler Creator Department of Mathematics College of Arts and Sciences Mathematical Modeling of Biological Processes at the Cellular, Tissue, and System Levels In this work, mathematical modeling is used in conjunction with in vivo and in vitro experiments to investigate disparate biological phenomena at various scales, including cell rounding, virus trapping, and drug delivery. First, a rapid change in cell morphology from a spread to a rounded state is modeled. This transition reveals a several-fold greater cell surface than is required to enclose a perfectly round object of the same volume, and an open question is how this extra surface is stored. A Hamiltonian model, where the energy cost is minimized, is used to address this question and reproduce statistics of the surface morphology. Next, antibody attachments and detachments to pathogens moving through a biological environment are modeled. Experiments demonstrate that a pathogen with absolutely no affinity to mucus can become trapped in a mucus network in the presence of antibodies. Antibodies and mucus work cooperatively to trap pathogens by tethering the pathogen to the mucus via the antibody. Both a continuum reaction-diffusion model and a stochastic model are used to simulate the pathogen and antibody movement and binding kinetics. This work generates many important insights into the design of antibodies that use trapping to protect against foreign pathogens infecting underlying tissue. Finally, the movement of a nanoparticle drug from organ to organ throughout the body is modeled. Covalently attaching polyethylene glycol (PEG) to a drug helps maintain an adequately high concentration in the blood. However, the anti-PEG antibodies increasingly common throughout the population attach to PEG and accelerate the elimination of PEGylated drugs. A possible strategy to temporarily lower the concentration of free anti-PEG antibodies is to introduce free PEG that will bind to free anti-PEG antibodies, thus depleting their numbers before the PEGylated drug treatment begins. This work uses a compartment model with local dynamics at different scales within different compartments to model the organ-specific changes in concentrations of the PEGylated drug, the free PEG, and the anti-PEG antibodies, as well as the binding kinetics. The results lay out guidelines for a nanoparticle PEGylated drug therapy. Spring 2017 2017 Applied mathematics eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Mathematics Mark Forest Thesis advisor Samuel Lai Thesis advisor Boyce Griffith Thesis advisor David Adalsteinsson Thesis advisor Katherine Newhall Thesis advisor text Timothy Wessler Creator Department of Mathematics College of Arts and Sciences Mathematical Modeling of Biological Processes at the Cellular, Tissue, and System Levels In this work, mathematical modeling is used in conjunction with in vivo and in vitro experiments to investigate disparate biological phenomena at various scales, including cell rounding, virus trapping, and drug delivery. First, a rapid change in cell morphology from a spread to a rounded state is modeled. This transition reveals a several-fold greater cell surface than is required to enclose a perfectly round object of the same volume, and an open question is how this extra surface is stored. A Hamiltonian model, where the energy cost is minimized, is used to address this question and reproduce statistics of the surface morphology. Next, antibody attachments and detachments to pathogens moving through a biological environment are modeled. Experiments demonstrate that a pathogen with absolutely no affinity to mucus can become trapped in a mucus network in the presence of antibodies. Antibodies and mucus work cooperatively to trap pathogens by tethering the pathogen to the mucus via the antibody. Both a continuum reaction-diffusion model and a stochastic model are used to simulate the pathogen and antibody movement and binding kinetics. This work generates many important insights into the design of antibodies that use trapping to protect against foreign pathogens infecting underlying tissue. Finally, the movement of a nanoparticle drug from organ to organ throughout the body is modeled. Covalently attaching polyethylene glycol (PEG) to a drug helps maintain an adequately high concentration in the blood. However, the anti-PEG antibodies increasingly common throughout the population attach to PEG and accelerate the elimination of PEGylated drugs. A possible strategy to temporarily lower the concentration of free anti-PEG antibodies is to introduce free PEG that will bind to free anti-PEG antibodies, thus depleting their numbers before the PEGylated drug treatment begins. This work uses a compartment model with local dynamics at different scales within different compartments to model the organ-specific changes in concentrations of the PEGylated drug, the free PEG, and the anti-PEG antibodies, as well as the binding kinetics. The results lay out guidelines for a nanoparticle PEGylated drug therapy. 2017-05 2017 Applied mathematics eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Mathematics Mark Forest Thesis advisor Samuel Lai Thesis advisor Boyce Griffith Thesis advisor David Adalsteinsson Thesis advisor Katherine Newhall Thesis advisor text Timothy Wessler Creator Department of Mathematics College of Arts and Sciences Mathematical Modeling of Biological Processes at the Cellular, Tissue, and System Levels In this work, mathematical modeling is used in conjunction with in vivo and in vitro experiments to investigate disparate biological phenomena at various scales, including cell rounding, virus trapping, and drug delivery. First, a rapid change in cell morphology from a spread to a rounded state is modeled. This transition reveals a several-fold greater cell surface than is required to enclose a perfectly round object of the same volume, and an open question is how this extra surface is stored. A Hamiltonian model, where the energy cost is minimized, is used to address this question and reproduce statistics of the surface morphology. Next, antibody attachments and detachments to pathogens moving through a biological environment are modeled. Experiments demonstrate that a pathogen with absolutely no affinity to mucus can become trapped in a mucus network in the presence of antibodies. Antibodies and mucus work cooperatively to trap pathogens by tethering the pathogen to the mucus via the antibody. Both a continuum reaction-diffusion model and a stochastic model are used to simulate the pathogen and antibody movement and binding kinetics. This work generates many important insights into the design of antibodies that use trapping to protect against foreign pathogens infecting underlying tissue. Finally, the movement of a nanoparticle drug from organ to organ throughout the body is modeled. Covalently attaching polyethylene glycol (PEG) to a drug helps maintain an adequately high concentration in the blood. However, the anti-PEG antibodies increasingly common throughout the population attach to PEG and accelerate the elimination of PEGylated drugs. A possible strategy to temporarily lower the concentration of free anti-PEG antibodies is to introduce free PEG that will bind to free anti-PEG antibodies, thus depleting their numbers before the PEGylated drug treatment begins. This work uses a compartment model with local dynamics at different scales within different compartments to model the organ-specific changes in concentrations of the PEGylated drug, the free PEG, and the anti-PEG antibodies, as well as the binding kinetics. The results lay out guidelines for a nanoparticle PEGylated drug therapy. 2017 Applied mathematics eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Mathematics Mark Forest Thesis advisor Samuel Lai Thesis advisor Boyce Griffith Thesis advisor David Adalsteinsson Thesis advisor Katherine Newhall Thesis advisor text 2017-05 Timothy Wessler Creator Department of Mathematics College of Arts and Sciences Mathematical Modeling of Biological Processes at the Cellular, Tissue, and System Levels In this work, mathematical modeling is used in conjunction with in vivo and in vitro experiments to investigate disparate biological phenomena at various scales, including cell rounding, virus trapping, and drug delivery. First, a rapid change in cell morphology from a spread to a rounded state is modeled. This transition reveals a several-fold greater cell surface than is required to enclose a perfectly round object of the same volume, and an open question is how this extra surface is stored. A Hamiltonian model, where the energy cost is minimized, is used to address this question and reproduce statistics of the surface morphology. Next, antibody attachments and detachments to pathogens moving through a biological environment are modeled. Experiments demonstrate that a pathogen with absolutely no affinity to mucus can become trapped in a mucus network in the presence of antibodies. Antibodies and mucus work cooperatively to trap pathogens by tethering the pathogen to the mucus via the antibody. Both a continuum reaction-diffusion model and a stochastic model are used to simulate the pathogen and antibody movement and binding kinetics. This work generates many important insights into the design of antibodies that use trapping to protect against foreign pathogens infecting underlying tissue. Finally, the movement of a nanoparticle drug from organ to organ throughout the body is modeled. Covalently attaching polyethylene glycol (PEG) to a drug helps maintain an adequately high concentration in the blood. However, the anti-PEG antibodies increasingly common throughout the population attach to PEG and accelerate the elimination of PEGylated drugs. A possible strategy to temporarily lower the concentration of free anti-PEG antibodies is to introduce free PEG that will bind to free anti-PEG antibodies, thus depleting their numbers before the PEGylated drug treatment begins. This work uses a compartment model with local dynamics at different scales within different compartments to model the organ-specific changes in concentrations of the PEGylated drug, the free PEG, and the anti-PEG antibodies, as well as the binding kinetics. The results lay out guidelines for a nanoparticle PEGylated drug therapy. 2017 Applied mathematics eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Mathematics Mark Forest Thesis advisor Samuel Lai Thesis advisor Boyce Griffith Thesis advisor David Adalsteinsson Thesis advisor Katherine Newhall Thesis advisor text 2017-05 Timothy Wessler Creator Department of Mathematics College of Arts and Sciences Mathematical Modeling of Biological Processes at the Cellular, Tissue, and System Levels In this work, mathematical modeling is used in conjunction with in vivo and in vitro experiments to investigate disparate biological phenomena at various scales, including cell rounding, virus trapping, and drug delivery. First, a rapid change in cell morphology from a spread to a rounded state is modeled. This transition reveals a several-fold greater cell surface than is required to enclose a perfectly round object of the same volume, and an open question is how this extra surface is stored. A Hamiltonian model, where the energy cost is minimized, is used to address this question and reproduce statistics of the surface morphology. Next, antibody attachments and detachments to pathogens moving through a biological environment are modeled. Experiments demonstrate that a pathogen with absolutely no affinity to mucus can become trapped in a mucus network in the presence of antibodies. Antibodies and mucus work cooperatively to trap pathogens by tethering the pathogen to the mucus via the antibody. Both a continuum reaction-diffusion model and a stochastic model are used to simulate the pathogen and antibody movement and binding kinetics. This work generates many important insights into the design of antibodies that use trapping to protect against foreign pathogens infecting underlying tissue. Finally, the movement of a nanoparticle drug from organ to organ throughout the body is modeled. Covalently attaching polyethylene glycol (PEG) to a drug helps maintain an adequately high concentration in the blood. However, the anti-PEG antibodies increasingly common throughout the population attach to PEG and accelerate the elimination of PEGylated drugs. A possible strategy to temporarily lower the concentration of free anti-PEG antibodies is to introduce free PEG that will bind to free anti-PEG antibodies, thus depleting their numbers before the PEGylated drug treatment begins. This work uses a compartment model with local dynamics at different scales within different compartments to model the organ-specific changes in concentrations of the PEGylated drug, the free PEG, and the anti-PEG antibodies, as well as the binding kinetics. The results lay out guidelines for a nanoparticle PEGylated drug therapy. 2017 Applied mathematics eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Mathematics Mark Forest Thesis advisor Samuel Lai Thesis advisor Boyce Griffith Thesis advisor David Adalsteinsson Thesis advisor Katherine Newhall Thesis advisor text 2017-05 Timothy Wessler Creator Department of Mathematics College of Arts and Sciences Mathematical Modeling of Biological Processes at the Cellular, Tissue, and System Levels In this work, mathematical modeling is used in conjunction with in vivo and in vitro experiments to investigate disparate biological phenomena at various scales, including cell rounding, virus trapping, and drug delivery. First, a rapid change in cell morphology from a spread to a rounded state is modeled. This transition reveals a several-fold greater cell surface than is required to enclose a perfectly round object of the same volume, and an open question is how this extra surface is stored. A Hamiltonian model, where the energy cost is minimized, is used to address this question and reproduce statistics of the surface morphology. Next, antibody attachments and detachments to pathogens moving through a biological environment are modeled. Experiments demonstrate that a pathogen with absolutely no affinity to mucus can become trapped in a mucus network in the presence of antibodies. Antibodies and mucus work cooperatively to trap pathogens by tethering the pathogen to the mucus via the antibody. Both a continuum reaction-diffusion model and a stochastic model are used to simulate the pathogen and antibody movement and binding kinetics. This work generates many important insights into the design of antibodies that use trapping to protect against foreign pathogens infecting underlying tissue. Finally, the movement of a nanoparticle drug from organ to organ throughout the body is modeled. Covalently attaching polyethylene glycol (PEG) to a drug helps maintain an adequately high concentration in the blood. However, the anti-PEG antibodies increasingly common throughout the population attach to PEG and accelerate the elimination of PEGylated drugs. A possible strategy to temporarily lower the concentration of free anti-PEG antibodies is to introduce free PEG that will bind to free anti-PEG antibodies, thus depleting their numbers before the PEGylated drug treatment begins. This work uses a compartment model with local dynamics at different scales within different compartments to model the organ-specific changes in concentrations of the PEGylated drug, the free PEG, and the anti-PEG antibodies, as well as the binding kinetics. The results lay out guidelines for a nanoparticle PEGylated drug therapy. 2017 Applied mathematics eng Doctor of Philosophy Dissertation Mathematics Mark Forest Thesis advisor Samuel Lai Thesis advisor Boyce Griffith Thesis advisor David Adalsteinsson Thesis advisor Katherine Newhall Thesis advisor text 2017-05 University of North Carolina at Chapel Hill Degree granting institution Timothy Wessler Creator Department of Mathematics College of Arts and Sciences Mathematical Modeling of Biological Processes at the Cellular, Tissue, and System Levels In this work, mathematical modeling is used in conjunction with in vivo and in vitro experiments to investigate disparate biological phenomena at various scales, including cell rounding, virus trapping, and drug delivery. First, a rapid change in cell morphology from a spread to a rounded state is modeled. This transition reveals a several-fold greater cell surface than is required to enclose a perfectly round object of the same volume, and an open question is how this extra surface is stored. A Hamiltonian model, where the energy cost is minimized, is used to address this question and reproduce statistics of the surface morphology. Next, antibody attachments and detachments to pathogens moving through a biological environment are modeled. Experiments demonstrate that a pathogen with absolutely no affinity to mucus can become trapped in a mucus network in the presence of antibodies. Antibodies and mucus work cooperatively to trap pathogens by tethering the pathogen to the mucus via the antibody. Both a continuum reaction-diffusion model and a stochastic model are used to simulate the pathogen and antibody movement and binding kinetics. This work generates many important insights into the design of antibodies that use trapping to protect against foreign pathogens infecting underlying tissue. Finally, the movement of a nanoparticle drug from organ to organ throughout the body is modeled. Covalently attaching polyethylene glycol (PEG) to a drug helps maintain an adequately high concentration in the blood. However, the anti-PEG antibodies increasingly common throughout the population attach to PEG and accelerate the elimination of PEGylated drugs. A possible strategy to temporarily lower the concentration of free anti-PEG antibodies is to introduce free PEG that will bind to free anti-PEG antibodies, thus depleting their numbers before the PEGylated drug treatment begins. This work uses a compartment model with local dynamics at different scales within different compartments to model the organ-specific changes in concentrations of the PEGylated drug, the free PEG, and the anti-PEG antibodies, as well as the binding kinetics. The results lay out guidelines for a nanoparticle PEGylated drug therapy. 2017 Applied mathematics eng Doctor of Philosophy Dissertation Mathematics Mark Forest Thesis advisor Samuel Lai Thesis advisor Boyce Griffith Thesis advisor David Adalsteinsson Thesis advisor Katherine Newhall Thesis advisor text 2017-05 University of North Carolina at Chapel Hill Degree granting institution Timothy Wessler Creator Department of Mathematics College of Arts and Sciences Mathematical Modeling of Biological Processes at the Cellular, Tissue, and System Levels In this work, mathematical modeling is used in conjunction with in vivo and in vitro experiments to investigate disparate biological phenomena at various scales, including cell rounding, virus trapping, and drug delivery. First, a rapid change in cell morphology from a spread to a rounded state is modeled. This transition reveals a several-fold greater cell surface than is required to enclose a perfectly round object of the same volume, and an open question is how this extra surface is stored. A Hamiltonian model, where the energy cost is minimized, is used to address this question and reproduce statistics of the surface morphology. Next, antibody attachments and detachments to pathogens moving through a biological environment are modeled. Experiments demonstrate that a pathogen with absolutely no affinity to mucus can become trapped in a mucus network in the presence of antibodies. Antibodies and mucus work cooperatively to trap pathogens by tethering the pathogen to the mucus via the antibody. Both a continuum reaction-diffusion model and a stochastic model are used to simulate the pathogen and antibody movement and binding kinetics. This work generates many important insights into the design of antibodies that use trapping to protect against foreign pathogens infecting underlying tissue. Finally, the movement of a nanoparticle drug from organ to organ throughout the body is modeled. Covalently attaching polyethylene glycol (PEG) to a drug helps maintain an adequately high concentration in the blood. However, the anti-PEG antibodies increasingly common throughout the population attach to PEG and accelerate the elimination of PEGylated drugs. A possible strategy to temporarily lower the concentration of free anti-PEG antibodies is to introduce free PEG that will bind to free anti-PEG antibodies, thus depleting their numbers before the PEGylated drug treatment begins. This work uses a compartment model with local dynamics at different scales within different compartments to model the organ-specific changes in concentrations of the PEGylated drug, the free PEG, and the anti-PEG antibodies, as well as the binding kinetics. The results lay out guidelines for a nanoparticle PEGylated drug therapy. 2017 Applied mathematics eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Mathematics Mark Forest Thesis advisor Samuel Lai Thesis advisor Boyce Griffith Thesis advisor David Adalsteinsson Thesis advisor Katherine Newhall Thesis advisor text 2017-05 Timothy Wessler Creator Department of Mathematics College of Arts and Sciences In this work, mathematical modeling is used in conjunction with in vivo and in vitro experiments to investigate disparate biological phenomena at various scales, including cell rounding, virus trapping, and drug delivery. First, a rapid change in cell morphology from a spread to a rounded state is modeled. This transition reveals a several-fold greater cell surface than is required to enclose a perfectly round object of the same volume, and an open question is how this extra surface is stored. A Hamiltonian model, where the energy cost is minimized, is used to address this question and reproduce statistics of the surface morphology. Next, antibody attachments and detachments to pathogens moving through a biological environment are modeled. Experiments demonstrate that a pathogen with absolutely no affinity to mucus can become trapped in a mucus network in the presence of antibodies. Antibodies and mucus work cooperatively to trap pathogens by tethering the pathogen to the mucus via the antibody. Both a continuum reaction-diffusion model and a stochastic model are used to simulate the pathogen and antibody movement and binding kinetics. This work generates many important insights into the design of antibodies that use trapping to protect against foreign pathogens infecting underlying tissue. Finally, the movement of a nanoparticle drug from organ to organ throughout the body is modeled. Covalently attaching polyethylene glycol (PEG) to a drug helps maintain an adequately high concentration in the blood. However, the anti-PEG antibodies increasingly common throughout the population attach to PEG and accelerate the elimination of PEGylated drugs. A possible strategy to temporarily lower the concentration of free anti-PEG antibodies is to introduce free PEG that will bind to free anti-PEG antibodies, thus depleting their numbers before the PEGylated drug treatment begins. This work uses a compartment model with local dynamics at different scales within different compartments to model the organ-specific changes in concentrations of the PEGylated drug, the free PEG, and the anti-PEG antibodies, as well as the binding kinetics. The results lay out guidelines for a nanoparticle PEGylated drug therapy. 2017 Applied mathematics eng Doctor of Philosophy Dissertation University of North Carolina at Chapel Hill Graduate School Degree granting institution Mark Forest Thesis advisor Samuel Lai Thesis advisor Boyce Griffith Thesis advisor David Adalsteinsson Thesis advisor Katherine Newhall Thesis advisor text 2017-05 Wessler_unc_0153D_17082.pdf uuid:24f25696-3698-45a3-b61c-26450fb9349e proquest 2017-04-25T17:03:26Z 2019-07-06T00:00:00 yes application/pdf 24070217