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dc.contributor.advisorSarkar, Susanta K.
dc.contributor.authorColomb, Warren A.
dc.date.accessioned2018-06-07T20:38:48Z
dc.date.accessioned2022-02-03T13:10:55Z
dc.date.available2018-06-07T20:38:48Z
dc.date.available2022-02-03T13:10:55Z
dc.date.issued2018
dc.identifierColomb_mines_0052E_11527.pdf
dc.identifierT 8523
dc.identifier.urihttps://hdl.handle.net/11124/172357
dc.descriptionIncludes bibliographical references.
dc.description2018 Spring.
dc.description.abstractThis thesis works towards the development of quantitative in vitro tissue models. The absence of quantitative three-dimensional (3D) in vitro models is a bottleneck in drug discovery and tissue engineering. To address this challenge, we intend to exploit the inherent randomness of cellular distributions to gain insights into cell-extracellular matrix (ECM) interactions. To achieve this goal, we need to first extract information from noisy data, correct for microscope drift, image thick 3D tissue models, and quantify random cellular distributions. This thesis has been organized into six chapters. Chapter one serves as an overview of the thesis, and provides the necessary background. Chapter two provides our work on noisy data analysis in the context of a detailed literature review. Chapter three presents a new method of estimating mechanical drift of microscopes, which utilizes an improved maximum likelihood method. Our method was shown to be valid in the presence of Gaussian and non-Gaussian noise to estimate the drift with both accuracy and precision within the range 1.55 5.75 nm. Chapter four presents our design and application of a lens-based light sheet microscope, which was used to image fluorescent beads and fluorescently labeled cells in agarose and alginate matrices with 3-micron depth resolution throughout a 1 cm thick sample. Our subcellular resolution across centimeter thick samples fills a niche area that has not been addressed by other microscope designs. Cellular distributions were modeled as a Poisson process, a process that has a constant probability of occurring in space or time. We hypothesize that if we start from a perfectly random tissue model, the underlying interactions of cells with the ECM will lead to deviations from a perfect Poisson process. These deviations will serve as quantitative biomarkers to define and characterize the tissue models. Chapter five discusses the preliminary results and issues on time resolved imaging of cellular distributions with the light sheet microscope. Finally, Chapter six presents future work, which builds on the techniques described in this thesis, towards quantifying Cell-ECM interactions.
dc.format.mediumborn digital
dc.format.mediumdoctoral dissertations
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado School of Mines. Arthur Lakes Library
dc.relation.ispartof2010-2019 - Mines Theses & Dissertations
dc.rightsCopyright of the original work is retained by the author.
dc.subjectextracellular matrix
dc.subjectmicroscopy
dc.subjectdrift
dc.subjectsingle molecule
dc.subjectlightsheet
dc.titleTowards quantification of cell-extracellular matrix interactions in tissue models using light sheet microscopy
dc.typeText
dc.contributor.committeememberKrebs, Melissa D.
dc.contributor.committeememberSquier, Jeff A.
dc.contributor.committeememberDurfee, Charles G.
thesis.degree.nameDoctor of Philosophy (Ph.D.)
thesis.degree.levelDoctoral
thesis.degree.disciplinePhysics
thesis.degree.grantorColorado School of Mines


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