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Computational modeling of nanoparticle distribution and toxicity in biological systems
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Mukherjee, Dwaipayan. Computational modeling of nanoparticle distribution and toxicity in biological systems. Retrieved from https://doi.org/doi:10.7282/T3M90BJ3

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TitleComputational modeling of nanoparticle distribution and toxicity in biological systems
NameMukherjee, Dwaipayan (author); Georgopoulos, Panos G. (chair); Pedersen, Henrik (internal member); Androulakis, Ioannis P. (internal member); Shapley, Nina (internal member); Gow, Andrew J. (outside member); Rutgers University; Graduate School - New Brunswick
Date Created2015
Other Date2015-05 (degree)
SubjectChemical and Biochemical Engineering, Nanoparticles, Nanostructures, Toxicology
Extent1 online resource (xxii, 220 p. : ill.)
DescriptionEngineered Nanoparticles are increasingly becoming a part of our daily lives due to their presence in an overwhelming majority of consumer products. Potential health risks due to chronic exposure to such particulate matter have not been properly evaluated. A multiscale, mechanistic, toxicodynamic model was developed as part of this dissertation, for studying the impact of inhaled nanoparticles on lung function in mammalian biological systems. The biologically-based model was developed in a modular fashion, with separate consideration given to NP distribution in the entire organism as well as various mechanisms at the cell, tissue, organ, and organism levels. Specifically the effect of inhaled nanoparticles on pulmonary function is evaluated and estimated based on resultant surfactant dysfunction. Pulmonary surfactant depletion is explicitly modeled by incorporating dynamics of surfactant constituents such as phospholipids and various lipoproteins. Various nanoparticle transformation processes such as agglomeration, dissolution, diffusion, and lipid adsorption inside biological systems, are explicitly considered and their effects on surfactant modification assessed. The model relates pulmonary mechanics at the organ level with cellular level surfactant dynamics in the lung, both of which are affected by nanoparticle inhalation. The model was evaluated with data from in vitro and in vivo measurements of surfactant levels, cell counts, and overall dynamic impedance in rodent lungs. The model was also extrapolated to adult humans and prediction of changes in pulmonary tissue resistance and elastance in humans are presented based on comparable one-time nanoparticle exposure. This is the first instance of a comprehensive modeling framework integrating research and mechanistic information regarding nanoparticle-biosystem interactions at multiple scales and linking pulmonary mechanisms and processes due to interaction with particulate matter with pulmonary function in human subjects.
NotePh.D.
NoteIncludes bibliographical references
Noteby Dwaipayan Mukherjee
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/T3M90BJ3
Languageeng
CollectionGraduate School - New Brunswick Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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