Degree
Doctor of Philosophy (PhD)
Department
Mechanical Engineering
Document Type
Dissertation
Abstract
The progression of various diseases is associated with alterations in the microenvironment of cells, consisting of a variety of metabolites like lipids and proteins. It is well known that lipids and proteins are potential biomarkers for indicating alterations within the cell microenvironment induced by disease, and various methods are frequently used for their examination. To understand the chemical composition and spatial distribution of constituents in tissues and cells, confocal Raman spectroscopy and microscopy, as non-destructive tools, have shown potential for monitoring abnormalities at the cellular level with high resolution and can facilitate detection through targeting multiple biomarkers. The application of Raman necessitates new analytical methods for enhancing biomarker detection to increase the accuracy of the evaluation. In this study, we have employed Raman spectroscopy and microscopy for multiplex imaging and characterizing malignant tissues. Using the acquired data, we applied empty modeling and Direct Classical Least Squares (DCLS) approaches to identify the chemical composition of biomarkers, specifically targeting lipids and proteins. Chapter one provides an introduction and review of Raman applications in disease detection. The methodology presented in Chapter 2 presents common methods used for all different projects, with a focus on empty modeling and the DCLS method as useful analytical approaches. In Chapter 3, we review the application of Raman microspectroscopy for the assessment of pancreatic cancer tumors before and after treatment. In this regard, we developed SERS nanotags to target three different proteins in the tumor microenvironment of pancreatic cancer, and by employing the empty modeling analysis method, we were able to simultaneously detect three biomarkers within tissues before and after treatment. In Chapter 4, we applied the DCLS analysis method to map lipid species remodeling within adipose tissues because of a high-fat diet. Using this label-free method, we were able to target ω-3 and ω-6 fatty acids within the tissues of low-fat and high-fat diets. In Chapter 5, we investigated the remodeling of lipid and protein species in triple-negative breast cancer tissues and normal tissues using Raman microspectroscopy. In these three projects, we employed other tools and imaging techniques to thoroughly assess and validate our findings.
Date
3-17-2025
Recommended Citation
Sheikh, Elnaz, "INVESTIGATING SPATIAL MAPPING OF LIPID AND PROTEIN ALTERATIONS WITHIN CELLS AND TISSUES USING RAMAN MICROSPECTROSCOPY" (2025). LSU Doctoral Dissertations. 6682.
https://repository.lsu.edu/gradschool_dissertations/6682
Committee Chair
Gartia, Manas
Included in
Bioimaging and Biomedical Optics Commons, Materials Science and Engineering Commons, Mechanical Engineering Commons, Nanoscience and Nanotechnology Commons
