The effects of mechanical forces on endothelial cell function and behavior are well documented, but have not been fully characterized. Specifically, fluid pressure has been shown to elicit physical and chemical responses known to be involved in the initiation and progression of endothelial cell-mediated vascularization. Central to the process of vascularization is the formation of tube-like structures. This process—tubulogenesis—is essential to both the physiological and pathological growth of tissues. Given the known effects of pressure on endothelial cells and its ubiquitous presence in the vasculature, we investigated pressure as a magnitude-dependent parameter for the regulation of endothelial tubulogenic activity. To accomplish this, we exposed two- and three-dimensional bovine aortic endothelial cell (BAEC) cultures to static pressures of 0, 20, and 40 mmHg for 3 and 4 days. The most significant findings were: (1) cells in two-dimensional culture exposed to 20, but not 40, mmHg exhibited significantly (p < 0.05) increased expression of both VEGF-C and VEGFR-3, and (2) cells in three-dimensional culture exposed to 20, but not 40, mmHg exhibited significant (p > 0.05) increases in endothelial sprouting. These findings evidence the utility of pressure as a selective modulator of tissue microvascularization in vitro and implicates pressure as factor in pathological tubulogenesis in vivo.

Older adults may have trouble when performing activities of daily living due to decrease in physical strength and degradation of neuromotor and musculoskeletal function. Motor activation patterns during Lateral Step Down and Step Up from 4-inch and 8-inch step heights was assessed in younger (n=8, 24.4 years) and older adults (n=8, 58.9 years) using joint angle kinematics and electromyography of lower extremity muscles. Ground reaction forces were used to ascertain the loading, stabilization and unloading phases of the tasks. Older adults had an altered muscle activation sequence and significantly longer muscle bursts during loading for the tibialis anterior, gastrocnemius, vastus medialis, bicep femoris, gluteus medius and gluteus maximus muscles of the stationary leg. They also demonstrated a significantly larger swing time (579.1 ms vs. 444.8 ms) during the step down task for the moving leg. The novel data suggests presence of age-related differences in motor coordination during lateral stepping.

Point-of-care testing (POCT) is defined as medical testing at or near the site of patient care and has become a critical component of the diagnostic industry. POCT has many advantages over tests in centralized laboratories including small reagent volumes, small size, rapid turnaround time, cost-effectiveness, low power consumption and functional integration of multiple devices. Paper-based POCT sensors are a new alternative technology for fabricating simple, low-cost, portable and disposable analytical devices for clinical diagnosis. The focus of this dissertation was to develop simple, rapid and low cost paper-based POCT sensors with high sensitivity and portability for disease biomarker detection. Lateral flow strips (LFS) were used as the basic platform as it provides several key advantages such as simplicity, fast response time, on site and cost-effectiveness, and it can be used to detect specific substances including small molecules, large proteins and even whole pathogens, in a sample by immunological reactions. Earlier designs of paper strips lacked the quantitative information of the analyte concentration and could only provide single analyte detection at a time. In this study, a series of modifications were made to upgrade the platform to compensate for these limitations. First, we developed a gold nanoparticle based LFS for qualitative colorimetrical detection of bladder cancer related biomarkers in standard solutions and in urine samples. Second, by incorporating an image processing program “ImageJ”, a semi-quantitative LFS platform was established. The capability of the strip was evaluated by testing a small DNA oxidative damage biomarker in urine and cell culture models. Third, we combined the electrochemical method and colorimetrical method for quantitative biomarker detection. Finally, we integrated a commercialized blood glucose meter to quantitatively detection of two non-glucose biomarkers by converting their signals to that of glucose. The upgraded sensor could provide a noninvasive, rapid, visual, quantitative and convenient detection platform for various disease biomarkers. In addition, this platform does not require expensive equipments or trained personnel, deeming it suitable for use as a simple, economical and portable field kit for on-site biomarker monitoring in a variety of clinical settings.

Personal computers and portable electronics continue to rapidly advance and integrate into our lives as tools that facilitate efficient communication and interaction with the outside world. Now with a multitude of different devices available, personal computers are accessible to a wider audience than ever before. To continue to expand and reach new users, novel user interface technologies have been developed, such as touch input and gyroscopic motion, in which enhanced control fidelity can be achieved. For users with limited-to-no use of their hands, or for those who seek additional means to intuitively use and command a computer, novel sensory systems can be employed that interpret the natural electric signals produced by the human body as command inputs. One of these novel sensor systems is the myoelectric detection circuit, which can measure electromyographic (EMG) signals produced by contracting muscles through specialized electrodes, and convert the signals into a usable form through an analog circuit. With the goal of making a general-purpose myoelectric detection circuit platform for computer interface applications, several electrical circuit designs were iterated using OrCAD software, manufactured using PCB fabrication techniques, and tested with electrical measurement equipment and in a computer simulation. The analog circuit design culminated in a 1.35” x 0.8” manufactured analog myoelectric detection circuit unit that successfully converts a measured EMG input signal from surface skin electrodes to a clean and usable 0-5 V DC output that seamlessly interfaces with an Arduino Leonardo microcontroller for further signal processing and logic operations. Multiple input channels were combined with a microcontroller to create an EMG interface device that was used to interface with a PC, where simulated mouse cursor movement was controlled through the voluntary EMG signals provided by a user. Functional testing of the interface device was performed, which showed a long battery life of 44.6 hours, and effectiveness in using a PC to type with an on-screen keyboard.

This thesis designed and fabricated various devices that were interfaced to an IC for an active contact lens that notifies the user of an event by detection of an external wireless signal. The contact lens consisted of an embedded antenna providing communication with a 2.4GHz system, as well as inductive charging at an operating frequency of 13.56 MHz. The lens utilized a CBC005 5µAh thin film battery by Cymbet and a manufactured graphene super capacitor as a power source. The custom integrated circuit (IC) was designed using the On Semiconductor CMOS C5 0.6 µm process to manage the battery and drive the display. A transparent, flexible, single cell display was developed utilizing electrochromic ink to indicate to the user of an event. Assembly of the components, encapsulation, and molding were implemented to create the final product. The material properties of the chosen substrate were analyzed for their clearness, flexibility, and biocompatibility to determine its suitability as a contact lens material. Finally, the two different fabrication techniques (microfabrication and screen printing) that were employed to make the devices are compared to determine the favorable process for each part of the system.

Functional vasodilation in arterioles is impaired with chronic ischemia. We sought to examine the impact of chronic ischemia and age on skeletal muscle resistance artery function. To examine the impact of chronic ischemia, the femoral artery was resected from young (2-3mo) and adult (6-7mo) mice and the profunda femoris artery diameter was measured at rest and following gracilis muscle contraction 14 days later using intravital microscopy. Functional vasodilation was significantly impaired in ischemic mice (14.4±4.6% vs. 137.8±14.3%, p<0.0001 n=8) and non-ischemic adult mice (103.0±9.4% vs. 137.8±14.3%, p=0.05 n=10). In order to analyze the cellular mechanisms of the impairment, a protocol was developed to apply pharmacological agents to the experimental preparation while maintaining tissue homeostasis. Endothelial and smooth muscle dependent vasodilation were impaired with ischemia, 39.6 ± 13.6% vs. 80.5 ± 11.4% and 43.0 ± 11.7% vs. 85.1 ± 10.5%, respectively. From this data, it can be supported that smooth muscle dysfunction is the reason for the observed impairment in arterial vasodilation.

Peripheral neuropathies are a set of common diseases that affect the peripheral nervous system, causing damage to vital connections between various parts of the body and the brain and spinal cord. Different clinical conditions are known to selectively impact various size nerve fibers, which often makes it difficult to diagnose which peripheral neuropathy a patient might have. The nerve conduction velocity diagnostic test provides clinically useful information in the diagnosis of some peripheral neuropathies. This method is advantageous because it tends to be minimally invasive yet it provides valuable diagnostic information. However, this test does not determine characteristics of peripheral nerve fiber size distributions, and therefore does not show any detailed information regarding the nerve fibers within the nerve trunk. Being able to determine which nerve fibers are contributing to the evoked potential within a nerve trunk could provide additional information to clinicians for the diagnosis of specific pathologies of the peripheral nervous system, such as chronic inflammatory demyelinating polyneuropathy or early diabetic peripheral neuropathy. In this study, three rat sciatic nerves are sectioned and stained with hematoxylin and eosin in order to measure the nerve fiber diameters within the nerve trunk. Stained samples are viewed using brightfield microscopy and images are analyzed using ImageJ. Histograms were created to show the frequency of various nerve fiber diameters. The nerve fiber diameters measured during this research are consistent with the range of previously published diameter values and will be used to support continuing research for a novel method to characterize peripheral nerve fiber size distributions using group delay.

Alzheimer’s disease (AD) is a chronic and progressive, irreversible syndrome that deteriorates the cognitive functions. Official death certificates of 2013 reported 84,767 deaths from Alzheimer’s disease, making it the 6th leading cause of death in the United States. The rate of AD is estimated to double by 2050. The neurodegeneration of AD occurs decades before symptoms of dementia are evident. Therefore, having an efficient methodology for the early and proper diagnosis can lead to more effective treatments. Neuroimaging techniques such as magnetic resonance imaging (MRI) can detect changes in the brain of living subjects. Moreover, medical imaging techniques are the best diagnostic tools to determine brain atrophies; however, a significant limitation is the level of training, methodology, and experience of the diagnostician. Thus, Computer aided diagnosis (CAD) systems are part of a promising tool to help improve the diagnostic outcomes. No publications addressing the use of Feedforward Artificial Neural Networks (ANN), and MRI image attributes for the classification of AD were found. Consequently, the focus of this study is to investigate if the use of MRI images, specifically texture and frequency attributes along with a feedforward ANN model, can lead to the classification of individuals with AD. Moreover, this study compared the use of a single view versus a multi-view of MRI images and their performance. The frequency, texture, and MRI views in combination with the feedforward artificial neural network were tested to determine if they were comparable to the clinician’s performance. The clinician’s performances used were 78 percent accuracy, 87 percent sensitivity, 71 percent specificity, and 78 percent precision from a study with 1,073 individuals. The study found that the use of the Discrete Wavelet Transform (DWT) and Fourier Transform (FT) low frequency give comparable results to the clinicians; however, the FT outperformed the clinicians with an accuracy of 85 percent, precision of 87 percent, sensitivity of 90 percent and specificity of 75 percent. In the case of texture, a single texture feature, and the combination of two or more features gave results comparable to the clinicians. However, the Gray level co-occurrence matrix (GLCOM), which is the combination of texture features, was the highest performing texture method with 82 percent accuracy, 86 percent sensitivity, 76 percent specificity, and 86 percent precision. Combination CII (energy and entropy) outperformed all other combinations with 78 percent accuracy, 88 percent sensitivity, 72 percent specificity, and 78 percent precision. Additionally, a combination of views can increase performance for certain texture attributes; however, the axial view outperformed the sagittal and coronal views in the case of frequency attributes. In conclusion, this study found that both texture and frequency characteristics in combinations with a feedforward backpropagation neural network can perform at the level of the clinician and even higher depending on the attribute and the view or combination of views used.

<p dir="ltr">The gastrointestinal (GI) tract and its diverse microbial community play a significant role in overall health, impacting various aspects such as metabolism, physiology, nutrition, and immune function. Disruptions in the gut microbiota have been associated with metabolic diseases, colorectal cancer, diabetes, obesity, inflammatory bowel disease, Alzheimer's disease, and depression. Despite recognizing the importance of the gut microbiota, the interrelationship between microbiota, diet, and disease prevention remains unclear. Current techniques for monitoring the microbiome often rely on fecal samples or invasive endoscopic procedures, limiting the understanding of spatial variations in the gut microbiota and posing invasiveness challenges. To address these limitations, this dissertation focuses on the design and development of an electronic-free smart capsule platform capable of targeted sampling of GI fluid within specific regions of the GI tract. The capsule can be retrieved for subsequent bacterial culture and sequencing analysis. The capsule design is based on stimuli-responsive polymers and superabsorbent hydrogels, chosen for their proven safety, compatibility, and scalability. By leveraging the pH variation across the GI tract, the pH-sensitive polymeric coatings dissolve at the desired region, activating the sampling process. The superabsorbent hydrogel inside the capsule collects the sampled GI fluid and facilitates capsule closure upon completion of sampling. Systematic studies were conducted to identify suitable pH-responsive polymer coatings, superabsorbent hydrogels, and processing conditions that effectively operated within the physiological conditions of the GI tract. The technology's effectiveness and safety were validated through rigorous <i>in vitro</i> and <i>in vivo</i> studies using pig models. These studies demonstrated the potential of the technology for targeted sampling of GI fluid in both small and large intestinal regions, enabling subsequent bacterial culture and gene sequencing analysis. Additionally, the capsule design was enhanced with the integration of a metal tracer, enabling traceability throughout the GI tract using X-ray imaging and portable metal detectors for ambulatory screening. This technology holds promise as a non-invasive tool for studying real-time metabolic and molecular interactions among the host, diet, and microbiota in challenging-to-access GI regions. Its application in clinical studies can provide new insights into diet-host-microbiome interactions and contribute to addressing the burden faced by patients and their families dealing with GI-related diseases.</p>

<p>    </p> <p>Cerebrovascular diseases, such as stroke, constitute the most common life-threatening neurological disease in the United States. To support normal brain function, maintaining adequate brain perfusion (i.e., cerebral blood flow (CBF)) is important. Therefore, it is crucial to assess the brain perfusion so that early intervention in cerebrovascular diseases can be applied if abnormal perfusion is observed. The goal of my study is to develop metrics to measure the brain perfusion through modeling brain physiology using resting-state and task-based blood-oxygenation-level- dependent (BOLD) functional MRI (fMRI). My first and second chapters focused on deriving the blood arrival time using the resting-state BOLD signal. In the first chapters, we extracted the systemic low-frequency oscillations (sLFOs) in the fMRI signal from the internal carotid arteries (ICA) and the superior sagittal sinus (SSS). Consistent and robust results were obtained across 400 scans showing the ICA signals leading the SSS signals by about 5 seconds. This delay time could be considered as an effective perfusion biomarker that is associate with the cerebral circulation time (CCT). To further explore sLFOs in assessing dynamic blood flow changes during the scan, in my second chapter, a “carpet plot” (a 2-dimensional plot time vs. voxel) of scaled fMRI signal intensity was reconstructed and paired with a developed slope-detection algorithm. Tilted vertical edges across which a sudden signal intensity change took place were successfully detected by the algorithm and the averaged propagation time derived from the carpet plot matches the cerebral circulation time. Given that CO₂ is a vasodilator, controlling of inhaled CO₂ is able to modulate the BOLD signal, therefore, as a follow-up study, we focused on investigating the feasibility of using a CO₂ modulated sLFO signal as a “natural” bolus to track CBF with the tool developed from the second chapter. Meaningful transit times were derived from the CO₂-MRI carpet plots. Not only the timing, the BOLD signal deformation (the waveform change) under CO₂ challenge also reveals very useful perfusion information, representing how the brain react to stimulus. Therefore, my fourth chapter focused on characterizing the brain reaction to the CO₂ stimulus to better measure the brain health using BOLD fMRI. Overall, these studies deepen our understanding of fMRI signal and the derived perfusion parameters can potentially be used to assess some cerebrovascular diseases, such as stroke, ischemic brain damage, and steno-occlusive arterial disease in addition to functional activations. </p>