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This dissertation is composed of two projects dedicated to the development of techniques and technologies for improving the quality of life for patients in both clinical and resource-limited settings. The purpose of the first project was to design a rapid diagnostic device to screen whole blood samples for the presence of infectious agents. Point-of-care (PoC) technologies are becoming increasingly important for the detection of infectious agents in resource-limited settings (RSLs) where state-of-the-art blood screening practices are not feasible for implementation. For this project, a rapid diagnostic device was developed to directly detect pathogen content within freshly drawn whole blood samples using a ligand-binding assay format. The assay is completely self-contained within a hermetically sealed device to minimize operational complexity and ensure operator safety. The diagnostic device is capable of processing complex sample matrices by selectively capturing, concentrating, and labeling infectious agents upon functionalized surfaces. Following sample processing, the assay is optically interrogated with a fluorescence-based reader to provide rapid feedback regarding sample purity. Designs of the rapid diagnostic platform evolved over several prototype generations corresponding to project milestones emphasizing ergonomic performance, military specification testing for environmental resilience, and manufacture to yield production-grade devices for future diagnostic performance data collection. The goal of the regenerative therapy-based portion of this research was to develop a novel technique for the selective enrichment of cells demonstrating enhanced regenerative capacity in tissue-extracted cell samples. Adherent cell cultures of stromal vascular fractions (SVFs) extracted from adipose tissues were exposed to nutrient deficient conditions' eliciting a bimodal cellular response between two dissimilar cell culture subpopulations. The regenerative capacity of the

As is the case with many ocular neuropathies, primary open-angle glaucoma (POAG) leads to an irreversible damage to the visual field. Loss of visual field first occurs in the peripheral vision and slowly propagates towards the middle. Although there are differences in its rate of incidence, glaucoma is projected to be the leading cause of blindness, second only to cataract, affecting significant percentage of populations across different age, race/ethnic groups. A hallmark of POAG is the dysfunction of retinal ganglion cells (RGCs) which connect to the axons which, in turn, relay the visual information from the eye to the brain. Previous research has shown that axonal density in the optic nerve head (ONH) is greatly reduced due to chronically elevated intraocular pressure (IOP). IOP-lowering treatment has been shown to reduce the visual field loss, and continues to be the dominant treatment methodology for glaucoma. Previous research has shown that the biomechanics of the lamina cribrosa (LC) - a highly porous tissue through which the axons carrying the visual information exit the eye, is important in influencing the viability of the RGCs. In a normal eye, the LC is primarily made up of collagen of types I, III, and IV which encompass (specifically, arranged circularly) the axon shafts and the blood vessels (1). In addition to elevated IOP, changes in the material properties of ocular tissues in and around the ONH region, which include peripapillary sclera and LC, could affect its biomechanics, which could be a result of changing microstructure and morphology of these tissues, and may contribute to POAG. The current work is aimed at creating computational models to incorporate the complex nature of ocular tissues, and develop computational techniques to characterize the variation in the material properties of ocular tissues (which include the tissue moduli, fiber orientation, permeability etc.), and study the effects they have on the biomechanical response of the LC

Hip fracture has long been considered as the most serious consequence of osteoporosis, which includes chronic pain, disability, and even death. In the elderly population, a femur fracture is very common. It is assessed that 50% of women aged 50 or older may experience a hip fracture in their remaining life. Hip fracture is among the most common injuries and can lead to substantial morbidity and mortality. In the US alone, over 250,000 hip fractures occur each year and this number is expected to double by the year 2040. Statistics indicate that over 20% of people who experience a hip fracture die within one year and only 25% have a total recovery. Femur fractures are now becoming a major social and economic burden on the health care system. In practice, it is very difficult to predict the femur fracture risks. One of the main reasons is that there is not a robust and easy-to-get measure to quantify the strength of the bone. Clinicians use bone mineral density (BMD) as an indicator of osteoporosis and fracture risk. Several studies showed that BMD cannot be used alone to identify bone strength. In fact, the majority of patients who suffer from fractures have normal or even higher BMD scores. There are a large number of risk factors that contribute to the occurrence of femur fracture, which should also be involved in predicting hip fracture risks. For example, age, weight, height, ethnicity and so on. Some of the factors might not have been identified yet. Thus, there will be a high level of uncertainty in the clinical dataset, which makes it difficult to construct and validate a hip risk prediction model. The objective of the dissertation is to construct an improved hip fracture risk prediction model. Due to the difficulty of obtaining experimental or clinical data, computational simulations might help increase the predictive ability of the risk model. In this research, the hip fracture risk model is based on a support vector machine (SVM) trained using a clinical dat

Abdominal Aortic Aneurysm (AAA) is a complex disease that leads to a localized dilation of the infrarenal aorta that develops over years. Longitudinal information in humans has been difficult to obtain for this disease, therefore mouse models have become increasingly used to study the development of AAAs. The objective of this study was to determine any changes that occur in the biomechanical response and fiber microstructure in the apolipoprotein E difficient (ApoE-/-) angiotensin II (AngII) infused mouse model of aneurysm during disease progression, as well as determine some of the underlying changes in biochemistry, and demonstrate a novel method of reducing any pathogenic protease activity. Using a Microbiaxial Opto-Mechanical Device (MOD), ex vivo studies included adult aortas of ApoE-/- AngII infused mice excised and tested for mechanical response simultaneously imaged using two-photon microscopy to assess the microstructure at multiple time points. In vitro and ex vivo studies have shown changes in protease concentrations with the use of FRET based proteolytic beacons able to provide a non-destructive method to quantify protease activity measured against mechanical and microstructural changes. In vitro studies have demonstrated protease activity can be reduced using a molecule providing a positive feedback mechanism for protease inhibition and possibly provide a reduction in aneurysm progression.

The purpose of this dissertation is to establish a unified theory of porohyperelasticity with transport and growth and to demonstrate the capability of this theory using a finite element model developed in MATLAB. The theory of volumetric growth is combined with the theory of mixed porohyperelasticity with transport and swelling (MPHETS) to derive a new method that models growth of biological soft tissues. The conservation equations and constitutive equations are developed for both solid-only growth and solid-fluid growth. An axisymmetric finite element framework is introduced for the new theory of growing MPHETS (GMPHETS). To demonstrate the difference of the GMPHETS model from a traditional hyperelastic (HE) growth model, several finite element test problems with example growth laws are considered, including time-dependent, concentration-dependent, and stress-dependent growth. In particular, this work demonstrates that the solid-only growth of an MPHETS model of a stylized artery results in a more uniform hoop stress than in a HE model under solid-only growth for the same amount of growth time using the same growth law. This may have implications in the context of developing residual stresses in soft tissues under intraluminal pressure. To my knowledge, this is the first description of an MPHETS model with growth. The developed computational framework can be used together with novel in-vitro and in-vivo experimental approaches to identify the governing growth laws for various soft tissues.