Date of Award

8-2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Bioengineering

Committee Chair/Advisor

Dr. Bruce Z. Gao

Committee Member

Dr. Delphine Dean

Committee Member

Dr. Dan Simionescu

Committee Member

Dr. Tong Ye

Abstract

Collagen is a critical component of the organization and one of the key factors contributing to the mechanical stability of the myocardium. Where cardiomyocytes actuate to contract the heart and deliver blood to the lungs and the entire body, the local collagen network must be able to support the mechanical needs of the heart by enhancing rigidity, reducing the mechanical responsibility of cells, and increasing compliance to add loading capacity during diastole. At an organ-wide level, this has been measured and modeled in many ways. At the tissue level, the mechanical properties have been evaluated using techniques such as bi-axial stretching. While very effective at approximating bulk properties, this cannot differentiate the contribution of cellular and sub-cellular elements, nor can they resolve mechanical properties smaller than a few millimeters. Without knowledge of molecular-level contributions to tissue biomechanics, it is difficult to formulate strategies for treating cardiovascular diseases that affect the mechanical pumping function of the heart. Modeling of the tissue has been done through high-resolution and three-dimensional imaging. While necessary, no mechanical data is included in these interpretations. Specifically, collagen has higher-order microforms that can be distinguished in high-resolution imaging, but its unique contributions within a mechanical framework have not been documented. Therefore, there is a need to have high-level morphological and mechanical data tied together to better model the sub-cellular contributions to myocardial mechanics. Atomic force microscopy is capable of meeting both of these needs: high-resolution mechanical data and topographical morphology. While effective, imaging is surface-bound and cannot tie in the relevance of the sub-surface composition. To address this problem, we designed an 'Omni-Modal' image registration technique capable of uniting mechanical data from the AFM with any optical technique. Furthermore, this technique must be able to image the biomolecules without labelling or fixative that bind to tissue elements and alter the mechanical behavior. Therefore, we utilize label-free Two-Photon Excitation Fluorescence and Second Harmonic Generation to prove this technique's translatability and support the ultrastructural data gathered and investigate the change in mechanical and morphological characteristics in response to fixation. This technique is capable of distinguishing multiple collagen microforms that exhibit unique mechanical contributions and morphology. We believe this technique can source a high-precision machine learning model that will be able to interpret the unique collagen geometries as mechanical vectors and thereby model the heart on a microscopic scale for both development and disease models.

Author ORCID Identifier

https://orcid.org/0000-0002-1537-9733

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