Project 5

Data Driven Models to Predict Therapeutic Delivery in the Presence of Lung Disease (Prof. Jessica Oakes) - The overarching goal of the Respiratory Innovation and Simulation Team (RESIST) is to engineer novel solutions to improve lung health. Our group combines experimental and numerical methods to predict fate of inhaled particles in the lung (e.g. cig/e-cig smoke and medications). Lung computer models must integrate clinical or experimental data in order to predict physiologically-realistic phenomenon. The goal of this project is link various asthmatic phenotypes with inability to treat with inhaled medications. The student will help in linking MRI and CT data with computational simulations to predict deposition patterns. Based on student interest, there may also be opportunities to work with in vivo models within the laboratory. Following this experience, the student will gain expertise in lung and asthma pathophysiology and developing and performing state-of-the-art computer simulations. This is a great opportunity to immerse yourself into a dynamic and growing research group.

 
Possible REU projects include:   

        • Creating realistic 3D airway geometries from CT scans of asthmatic subjects.

        • Integrating hyper-polarized MRI scans with the airway geometries to model gas flow in the         lung.

        • Track particles throughout the respiration cycle to predict hotspots.

        • Analyze results and correlate findings with various asthma phenotypes (e.g. airway         morphology, pulmonary function tests, and various bio-markers).

Project 6

Identification of Functional Forms and Estimation of Material Parameters in a Computational Model of Arterial Growth and Remodeling (Prof. Chiara Bellini) - Stiffening of central arteries is an independent risk factor for cardiovascular disease that naturally occurs with age but can be accelerated by lifestyle habits, disease, or medications to treat viral infections, autoimmune diseases, and cancer. Elastic fibers fragmentation, imbalance between deposition and removal of collagen, improper organization of collagen fibers, and cell apoptosis are only a few of the microstructural changes that associate with a decline in vascular function. Characterizing the correlation between microstructural remodeling and changes in tissue stiffness might identify potential targets for treatment. The overall goal of the project is to use biaxial mechanical data and results from histology/immunohistochemistry on fixed aortic specimens to inform and validate a computational model that describes the evolution of aortic wall structure and function following specific electro-chemo-mechanical stimuli.

Possible REU projects include: 

        • Analyzing biaxial mechanical data to estimate the material parameters that characterize the         mechanical response of the aorta at fixed time points. A nonlinear least square regression will         be used to minimize an objective function that accounts for the difference between         experimental data and numerical predictions;

        • Analyzing histological/immunohistochemical data to identify functional forms that describe         the synthesis of new extracellular matrix proteins and the inward migration or proliferation of         cells as well as the degradation/loss of mechanically competent structural proteins and the         outward migration or apoptosis of cells.