Endothelial cells, which form the inner layer of the vasculature, constantly interact with their external microenvironment called the extracellular matrix (ECM) by exerting contractile cell-substrate stresses called tractions and cell-cell stresses called intercellular stresses. This cellular mechanosensing can become aberrant and act as a precursor for many vascular pathological and physiological processes such as cancer metastasis, atherosclerosis, cell differentiation, migration, and morphogenesis. Also, intracellular calcium signalling plays an important role in endothelial cell motility and in maintaining vascular tone. Alteration in ECM composition has been linked to several pathologies, in fact, a transition to a fibronectin-rich matrix from a type I collagen-rich and elastin-rich matrix in coronary artery disease, for example. However, the influence of ECM compositions and intracellular calcium levels on cell mechanics is not clearly understood. The first study will shed light on ECM composition and its influence on endothelial mechanical properties including traction, intercellular stresses, cell velocity, and various morphological parameters. The second study will enhance our knowledge on the role calcium signaling plays on cellular tractions. The final chapters will focus on the development and utilization of Machine Learning (ML) models for the predictions of tractions and intercellular stresses with morphological and pharmacological predictors, which to our knowledge is the first work in the field. The results yielded from this work will further our understanding of cellular mechanics at the mesoscale by: i) Identifying the role of specific ECM molecules in mechanical signaling, ii) Understanding the influence of transient calcium signaling on tractions, and iii) Providing a machine learning framework that can be used for the prediction of tractions and intercellular stresses as a dose dependent response to a drug that is known to influence cell mechanics. These findings will be beneficial to drug development studies and targeted drug therapy for treating various vascular-related pathologies.
| Identifer | oai:union.ndltd.org:ucf.edu/oai:stars.library.ucf.edu:etd2020-1768 |
| Date | 01 January 2021 |
| Creators | Subramanian Balachandar, Vignesh Aravind |
| Publisher | STARS |
| Source Sets | University of Central Florida |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Electronic Theses and Dissertations, 2020- |
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