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Author ORCID Identifier
https://orcid.org/0000-0002-3442-7702
AccessType
Open Access Dissertation
Document Type
dissertation
Degree Name
Doctor of Philosophy (PhD)
Degree Program
Chemistry
Year Degree Awarded
2021
Month Degree Awarded
September
First Advisor
Richard Vachet
Subject Categories
Analytical Chemistry
Abstract
Nanomaterial delivery systems constitute a group of drug delivery vehicles that have been used extensively in biodelivery. The proper characterization of the therapeutic function of these nanomaterials requires analytical methods to track the presence of the cargo and its biochemical effects. In some cases, the detection of the cargo and biochemical changes are not attainable in the same experiment, and more than one technique might be needed for the proper analysis of the drug delivery system. In this case, separate analysis of adjacent tissue sections is performed by techniques that offer complementary information such as MALDI-MS and LA-ICP-MS. However, the approaches to combine the information from these techniques to obtain insights into the mechanism of action of the nanomaterials have been limited to visual inspection and image overlay, which can only provide qualitative information. To advance towards a more quantitative analysis, in this dissertation we have developed computational techniques for image reconstruction, segmentation, and registration of MALDI-MS and LA-ICP-MS images to monitor the biodistribution, excretion and biochemical effects of nanomaterial delivery systems. First, we developed an open-source computational approach for LA-ICP-MS image reconstruction and segmentation using Python, which revealed that nanomaterials distribute in different sub-organ regions based on their chemical and physical properties. For instance, in the analysis of gold nanoparticles and bismuth nanorods, we find that the nanomaterials distribute in different regions of the spleen, suggesting differences in their biochemical interactions within the same organ. Next, we developed a computational workflow in Python to register LA-ICP-MS and MALDI-MS images using image registration approaches, obtaining a method with errors below 50 µm. Finally, we used the developed approaches for registration of LA-ICP-MS and MALDI-MS images to evaluate the delivery vehicles and cargo, obtaining quantitative information about the correlation of the signals obtained in the two image modalities. The use of image registration for the analysis of siRNA delivery via nanoparticle stabilized capsules (NPSC) reveals that expected changes in lipid levels occur at different locations than the NPSC accumulate, thus providing deeper insight into how siRNA delivery by NPSCs influences lipid biochemistry in vivo.
DOI
https://doi.org/10.7275/24366398
Recommended Citation
Castellanos, Laura J., "Computational approaches for the multimodal imaging of nanomaterials and their biochemical effects" (2021). Doctoral Dissertations. 2290.
https://doi.org/10.7275/24366398
https://scholarworks.umass.edu/dissertations_2/2290
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