A reliable method for real-time blood flow monitoring in vivo is critical for several medical applications, including monitoring cardiovascular diseases, evaluating interventional procedures and surgeries, and increasing the safety and efficacy of neuromodulation procedures. High-speed methods are particularly necessary for neural monitoring, due to the brain's heightened sensitivity to hypoxic and ischemic conditions. High-speed CBF monitoring methods may also provide a useful biomarker for the development of a closed-loop deep brain stimulation (DBS) system. Current methods such as laser Doppler, bold fMRI, and positron emission tomography (PET) often involve cumbersome instrumentation and are therefore not well- suited for chronic microvasculature monitoring. The purpose of this study is to develop a method for real-time measurement of blood flow changes using electrochemical impedance spectra (EIS). Utilizing EIS to measure CBF has the potential to be included in a chronic, closed-loop DBS system that is modulated by fluctuations in CBF, using minimal additional instrumentation. Five experiments in rodents were conducted, with the objective of 1) determining whether electrochemical impedance spectra showed impedance changes correlated with changes in blood flow, assessing the sensitivity, specificity, and limitations of detection of this method, and 2) determining whether cyclic voltammetry-based method could be used to produce EIS more rapidly than current methods. The experimental set-up included electrodes in the femoral artery with the administration of endothelin (ET-1) to induce blood flow changes (N=1), electrodes in the motor cortex using isoflurane variation to induce blood flow changes (N=3), and electrodes in the femoral artery with the administration of nitroglycerin (NTG) to induce blood flow changes (N=1). Preliminary results suggest that impedance changes in the higher frequencies (over 160 Hz) demonstrated higher sensitivity to blood flow changes in the femoral artery model compared to <100 Hz frequencies, with inconclusive results in the motor cortex model. Future in vivo experiments will be conducted using endothelin-1 to further establish the relationship between impedance and cerebral blood flow in the brain.

Allogeneic islet transplantation has the potential to reverse Type 1 Diabetes in patients. However, limitations such as chronic immunosuppression, islet donor numbers, and islet survival post-transplantation prevent the widespread application of allogeneic islet transplantation as the treatment of choice. Macroencapsulation devices have been widely used in allogeneic islet transplantation due to their capability to shield transplanted cells from the immune system as well as provide a supportive environment for cell viability, but macroencapsulation devices face oxygen transport challenges as their geometry increases from preclinical to clinical scales. The goal of this work is to generate complex 3D hydrogel macroencapsulation devices with sufficient oxygen transport to support encapsulated cell survival and generate these devices in a way that is accessible in the clinic as well as scaled manufacturing. A 3D-printed injection mold has been developed to generate hydrogel-based cell encapsulation devices with spiral geometries. The spiral geometry of the macroencapsulation device facilitates greater oxygen transport throughout the whole device resulting in improved islet function in vivo in a syngeneic rat model. A computational model of the oxygen concentration within macroencapsulation devices, validated by in vitro analysis, predicts that cells and islets maintain a greater viability and function in the spiral macroencapsulation device. To further validate the computational model, pO2 Reporter Composite Hydrogels (PORCH) are engineered to enable spatiotemporal measurement of oxygen tension within macroencapsulation devices using the Proton Imaging of Siloxanes to map Tissue Oxygenation Levels (PISTOL) magnetic resonance imaging approach. Overall, a macroencapsulation device geometry designed via computational modeling of device oxygen gradients and validated with magnetic resonance (MR) oximetry imaging enhances islet function and survival for islet transplantation.

Cardiovascular diseases (CVDs) are the leading cause of mortality worldwide, causing nearly 25% of deaths in the United States. Despite the efforts to create in vitro models for the study and treatment of CVDs, these are still limited in their recapitulation of the heart tissue. Thus, the engineering of accurate cardiac models is imperative to gain more understanding and improve the outcome of CVDs. This Ph.D. dissertation focuses on the development and characterization of isogenic cardiac organoids derived from human induced pluripotent stem cells (hiPSCs). Additionally, the integration of chemical and biological cues for enriching their microenvironment and promoting their maturation state and function were studied. First, hiPSC-derived cardiac cells were utilized for the fabrication of multicellular spherical microtissues, namely isogenic cardiac organoids. The cellular composition and culture time of the engineered tissues were optimized to induce cellular aggregation and the formation of cell-cell interactions. Also, ribbon-like gold nanoparticles, namely gold nanoribbons (AuNRs), were synthesized, characterized, and biofunctionalized for their integration into the isogenic cardiac organoids. In-depth biological evaluation of the organoids showed enhanced cardiac maturation markers. Furthermore, a supplement-free cell culture regime was designed and evaluated for fabricating isogenic cardiac organoids. Mechanistic, cellular, and molecular-level studies demonstrated that the presence of hiPSC-derived cardiac fibroblasts (hiPSC-CFs) significantly improves the morphology and gene expression profile of the organoids. Electrophysiological-relevant features of the organoids, such as conduction velocity (CV), were further investigated utilizing a microelectrode array (MEA) platform. It was shown that MEA offers a simple, yet powerful approach to assessing electrophysiological responses of the tissues, where a trend in decreased CV was found due to the presence of hiPSC-CFs. Overall, this dissertation has a broad impact casting light on the development strategy and biological mechanisms that govern the formation and function of isogenic cardiac organoids. Moreover, this study presents two unique approaches to promote maturation of stem cell-derived cardiac organoids: 1) through the integration of novel biofunctionalized nanomaterials, and 2) through a cell culture regime, leading to enhanced function of the organoids. The proposed micro-engineered organoids have broad applications as physiologically relevant tissues for drug discovery, CVDs modeling, and regenerative medicine.

Little is known about how cognitive and brain aging patterns differ in older adults with autism spectrum disorder (ASD). However, recent evidence suggests that individuals with ASD may be at greater risk of pathological aging conditions than their neurotypical (NT) counterparts. A growing body of research indicates that older adults with ASD may experience accelerated cognitive decline and neurodegeneration as they age, although studies are limited by their cross-sectional design in a population with strong age-cohort effects. Studying aging in ASD and identifying biomarkers to predict atypical aging is important because the population of older individuals with ASD is growing. Understanding the unique challenges faced as autistic adults age is necessary to develop treatments to improve quality of life and preserve independence. In this study, a longitudinal design was used to characterize cognitive and brain aging trajectories in ASD as a function of autistic trait severity. Principal components analysis (PCA) was used to derive a cognitive metric that best explains performance variability on tasks measuring memory ability and executive function. The slope of the integrated persistent feature (SIP) was used to quantify functional connectivity; the SIP is a novel, threshold-free graph theory metric which summarizes the speed of information diffusion in the brain. Longitudinal mixed models were using to predict cognitive and brain aging trajectories (measured via the SIP) as a function of autistic trait severity, sex, and their interaction. The sensitivity of the SIP was also compared with traditional graph theory metrics. It was hypothesized that older adults with ASD would experience accelerated cognitive and brain aging and furthermore, age-related changes in brain network topology would predict age-related changes in cognitive performance. For both cognitive and brain aging, autistic traits and sex interacted to predict trajectories, such that older men with high autistic traits were most at risk for poorer outcomes. In men with autism, variability in SIP scores across time points trended toward predicting cognitive aging trajectories. Findings also suggested that autistic traits are more sensitive to differences in brain aging than diagnostic group and that the SIP is more sensitive to brain aging trajectories than other graph theory metrics. However, further research is required to determine how physiological biomarkers such as the SIP are associated with cognitive outcomes.

Glioblastoma brain tumors are among the most lethal human cancers. Treatment efforts typically involve both surgical tumor removal, as well as ongoing therapy. In this work, we propose the use of deuterium magnetic resonance imaging (MRI) to delineate tumor boundaries based on spatial distributions of deuterated leucine, as well as resolve the metabolism of leucine within the tumor. Accurate boundary identification contributes to effectiveness of tumor removal efforts, while amino acid metabolism information may help characterize tumor malignancy and guide ongoing treatment. So, we first examine the fundamental mechanisms of deuterium MRI. We then discuss the use of spin-echo and gradient recall echo sequences for mapping spatial distributions of deuterated leucine, and the use of single-voxel spectroscopy for imaging metabolites within a tumor.

Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive technique that offers a unique ability to provide the spatial distribution of relevant biochemical compounds (metabolites). The ‘spectrum’ of information provided by MRSI is used as biomarkers for the differential diagnosis of several diseases such as cancer or neurological disorders. Treatment responsive brain tumors can appear similar to non-responsive tumors on conventional anatomical MR images, earlier in the therapy, leading to a poor prognosis for many patients. Biomarkers such as lactate are particularly of interest in the oncological studies of solid tumors to determine their energy metabolism, blood flow, and hypoxia. Despite the capability of nearly all clinical MRI scanners to perform MRSI only limited integration of MRSI into routine clinical studies has occurred to date. The major challenges affecting its true potential are the inherently long acquisition time, low signal-to-noise (SNR) of the signals, overlapping of spectral lines, or the presence of artifacts. The goal of this dissertation work is to facilitate MRSI in routine clinical studies without affecting the current patient throughput. In this work, the Compressed Sensing (CS) strategy was used to accelerate conventional Point RESolved Spectroscopy (PRESS) MRSI by sampling well below the Shannon-Nyquist limit. Two undersampling strategies, namely the pseudo-random variable density and a novel a priori method was developed and implemented on a clinical scanner. Prospectively undersampled MRSI data was acquired from patients with various brain-related concerns. Spatial-spectral post-processing and CS reconstruction pipeline was developed for multi-channel undersampled data. The fidelity of the CS-MRSI method was determined by comparing the CS reconstructed data to the fully sampled data. Statistical results showed that the a priori approach maintained high spectral fidelity compared to the fully sampled reference for an 80% reduction in scan time. Next, an improvement to the CS-MRSI reconstruction was achieved by incorporating coil sensitivity maps as support in the iterative process. Further, a CS-MRSI-based fast lactate spectroscopic imaging method was developed and implemented to achieve complete water and fat suppression for accurate spatial localization and quantification of lactate in tumors. In vitro phantoms were developed, and the sequence was tested to determine the efficacy of CS-MRSI for low SNR signals, the efficacy of the CS acceleration was determined with statistical analysis.

This thesis describes the development, characterization, and application of new biomedical technologies developed around the photoacoustic effect. The photoacoustic effect is defined as optical absorption-based generation of ultrasound and provides the foundation for a unique method of imaging and molecular detection. The range of applications of the photoacoustic effect have not yet been fully explored. Photoacoustic endoscopy (PAE) has emerged as a minimally invasive tool for imaging internal organs and tissues. One of the main themes of this dissertation involves the first reported dual-intrauterine photoacoustic and ultrasound deep-tissue imaging endoscope. This device was designed to enable physicians at the point-of-care to better elucidate overall gynecological health, by imaging the lining of the human uterus. Intrauterine photoacoustic endoscopy is made possible due to the small diameter of the endoscope (3mm), which allows for complete, 360-degree organ analysis from within the uterine cavity. In certain biomedical applications, however, further minimization is necessary. Sufficiently small diameter endoscopes may allow for the possibility of applying PAE in new areas. To further miniaturize the diameter of our endoscopes, alternative imaging probe designs were investigated. The proposed PAE architecture utilizes a hollow optical waveguide to allow for concentric guiding of both light and sound. This enables imaging depths of up to several millimeters into animal tissue while maintaining an outer diameter of roughly 1mm. In the final focus of this dissertation, these waveguides are further investigated for use in micropipette electrodes, common in the field of single cell electrophysiology. Pulsed light is coupled with these electrodes providing real-time photoacoustic feedback, useful in navigation towards intended targets. Lastly, fluorescence can be generated and collected at the micropipette aperture by utilizing an intra-electrode tapered optical fiber. This allows for a targeted robotic approach to labeled neurons that is independent of microscopy.

Current culturing methods allow for human neural progenitor cells to be differentiated into neurons for use in diagnostic tools and disease modeling. An issue arises in the relatively low number of cells that can be successfully expanded and differentiated using these current methods, making the progress of research dependent on these cultures as a large number of cells are needed to conduct relevant assays. This project focuses on the expansion and differentiation of human neural progenitor cells cultured on microcarriers and within a rotating bioreactor system as a way to increase the total number of cells generated. Additionally, cryopreservation and the characteristics of these neurons post thaw is being investigated to create a way for long term storage, as well as, a method for standardizing cell lines between multiple experiments at different time points. The experiments covered in this study are aimed to compare the characteristics of differentiated human neurons, both demented and non-demented cell lines between pre-cryopreservation, freshly differentiated neurons and post-cryopreservation neurons. The assays conducted include immunofluorescence, calcium imaging, quantitative polymerase chain reaction, flow cytometry and ELISA data looking at Alzheimer’s disease traits. With the data collected within this study, the use of bioreactors, in addition to, cryopreservation of human neurons for long term storage can be better implemented into human neural progenitor cell research. Both of these aspects will increase the output of these cultures and potentially remove the bottleneck currently found within human neural disease modeling.

Cell viability is an important assessment in cell culture to characterize the health of the cell population and confirm if cells are alive. Morphology or end-line assays are used to determine cell viability of entire populations. Intracellular pO2 levels is indicative of cell health and metabolism that can be used as a factor to asses cell viability in an in-line assay. Siloxane based pO2 sensing nanoprobes present a modality to visualize intracellular pO2. Using fluorescent lifetime imaging microscopy (FLIM), pO2 levels can be mapped intracellular as a highly functional in-line assay for cell viability. FLIM is an imaging modality that reconstructs an image based of its fluorescent lifetime. Nanoprobes were synthesized in different manufacturing/storage conditions. The nanoprobes for both long- and short-term storage were characterized in a cell free environment testing for changes in fluorescent intensity, average and maximum nanoprobe diameter. The nanoprobes were validated in two different culture systems, 2D and microcarrier culture systems, for human derived neural progenitor cells (NPCs) and neurons. Long- and short-term storage nanoprobes were used to label different neuronal based culture systems to asses labeling efficiency through fluorescent microscopy and flow cytometry. NPCs and neurons in each culture system was tested to see if nanoprobe labeling effected cellular phenotype for traits such as: cell proliferation, gene expression, and calcium imaging. Long-term and short-term storage nanoprobes were successfully validated for both NPCs and neurons in all culture systems. Assessments of the pO2 sensing nanoprobes will be further developed to create a highly functional and efficient in-line test for cell viability.

Solid tumors advance from benign stage to a deadly metastatic state due to the complex interaction between cancer cells and tumor microenvironment (TME) including stromal cells and extracellular matrix (ECM). Multiple studies have demonstrated that ECM dysregulation is one of the critical hallmarks of cancer progression leading to formation of a desmoplastic microenvironment that participates in tumor progression. Cancer associated fibroblasts (CAFs) are the predominant stromal cell type that participates in desmoplasia by depositing matrix proteins and increasing ECM stiffness. Although the influence of matrix stiffness on enhanced tumorigenicity has been well studied, the biological understanding about the dynamic changes in ECM architecture and the role of cancer-stromal cell interaction on ECM remodeling is still limited.

In this dissertation, the primary goal was to develop a comprehensive cellular and molecular level understanding of ECM remodeling due to the interaction of breast tumor cells and CAFs. To that end, a novel three-dimensional (3D) high-density tumor-stroma model was fabricated in which breast tumor cells (MDA-MB-231 and MCF7) were spatially organized surrounded by CAF-embedded collagen-I hydrogel (Aim 1). Further the platform was integrated with atomic force microscopy to assess the dynamic changes in ECM composition and stiffness during active tumor invasion. The results established an essential role of crosstalk between breast tumor cells and CAFs in ECM remodeling. The studies were further extended by dissecting the mode of interaction between tumor cells and CAFs followed by characterization of the role of various tumor secreted factors on ECM remodeling (Aim 2). The results for the first time established a critical role of paracrine signaling between breast tumor cells and CAFs in modulating biophysical properties of ECM. More in-depth analysis highlighted the role of tumor secreted cytokines, specifically PDGF-AA/BB, on CAF-induced desmoplasia. In aim 3, the platform was further utilized to test the synergistic influence of anti-fibrotic drug (tranilast) in conjugation with chemotherapeutic drug (Doxorubicin) on desmoplasia and tumor progression in the presence of CAFs. Overall this dissertation provided an in-depth understanding on the impact of breast cancer-stromal cell interaction in modulating biophysical properties of the ECM and identified the crucial role of tumor secreted cytokines including PDGF-AA/BB on desmoplasia.