A persistent limitation to current and future anti-cancer therapies is an inability to deliver high levels of active agent throughout the entire target tumor tissue volume without adversely impacting normal tissues. Interstitial transport is compromised by the poor mobility of macromolecules and nanoscale structures. We developed an in vitro system to quantify the facilitated transport of superparamagnetic (SPM) nanoparticles (NPs) through model extracellular matrix (ECM) in vitro. SPM NP motion was induced by an external magnetic field. 135 nm radius NPs with a polyethylene glycol (PEG) surface moved through the ECM with an average velocity of 1.5 mm h-1, a velocity suitable for some clinical applications. Steric barriers such as collagen I sharply limit interstitial delivery of macromolecular and nanoparticle-based therapeutic agents. Collagenase-linked SPM NPs overcame these barriers and moved through ECM in vitro at 90 ìm hr-1, a rate similar to invasive cells, under the influence of a magnetic field. Temporal decay of collagenase activity shifted from an exponential behavior in solution to a linear relationship when NP-attached. NP platforms offer the opportunity to develop a unified synthesis method for formation of multifunctional agents. We have demonstrated a facile method of conjugating multiple enzyme species to a NP via sulfhydryl-maleimide reaction chemistry. Horseradish peroxidase, á-glucosidase, and collagenase were simultaneously conjugated to the 300 Da PEG surface of SPM NPs at 15:1, 127:1 and 103:1 functional enzyme:NP ratio, respectively. SATP addition of sulfhydryl groups to each enzyme was achieved without significant reduction in enzyme activity. Cross reactivity of enzymes between enzyme activity assay systems was negligible. Multifunctional NPs mimic complex invasive biological processes found in metastatic invasion and immune cell interactions. Isolated study of sets of enzymes in an invasion experimental system may make an ideal screening tool for blocking pathogenic invasive processes, including cancer metastasis and abnormal angiogenesis. Dispersion of otherwise immobile macromolecular or nanoscale therapeutic structures can be achieved with the proteolytic SPM NP carriers detailed in this work.

Our brains process and interpret sensory information in order to generate perceptions of the environment or motivate behavior. However, the underlying mechanisms by which salient stimulus qualities are represented by neuronal response patterns remain a mystery. Precise coordination of spike events, or synchrony, is an attractive candidate to play a role in (visual) coding since it exists among (visual) cortical neurons, but its functional significance is largely unknown. Proving synchrony's importance in signaling is difficult since adequate methods to measure synchrony have not been developed. Current approaches quantify synchrony as a relationship between two neurons. However, synchrony allows for the formation of transient functional groups which could include tens, hundreds, thousands, or even larger numbers of neurons. Furthermore, very few studies have investigated how to measure the quality of synchrony in an assembly as well as develop some means to display these quantities. <br>      The work presented here derives a measure for synchrony within assemblies of arbitrary size by modeling the biological process of postsynaptic potential integration. We derive measures for the magnitude and quality of synchrony as well as show how our results are consistent with the Joint Peri-Stimulus Time Histogram approach for assemblies of two neurons. We also evaluate synchrony's role as a possible neural substrate for contour integration by investigating dynamic grouping and characteristics of group membership. Finally, we propose future investigation of synchrony as a biological sparse code employed by the visual cortex to represent high-order stimulus features in natural scenes.

A notable complication of applying current image-guided surgery techniques of soft tissue to kidney resections (nephrectomies) is the limited field of view of the intraoperative kidney surface. This limited view constrains the ability to obtain a geometrically descriptive surface for accurate surface-based registrations. Examining the affects of the limited view involved using two orientations of a kidney phantom to model typical laparoscopic and open partial nephrectomy views. Point-based registrations, using either rigidly attached markers or anatomical landmarks as fiducials, served as initial alignments for surface-based registrations. Laser range scanner (LRS) obtained surfaces were registered to the phantom's image surface using a rigid iterative closest point algorithm. Subsets of each orientations LRS surface were used in a robustness test to determine which parts of the surface can accurately predict registrations for the entire surface. Results suggest that obtaining accurate registrations is a function of the percentage of the total surface and of geometric surface properties, such as curvature. Approximately 30% of the total image surface is required, regardless of the location of that surface subset. However, that percentage decreases when the surface subset contains information from opposite ends of the surface and/or unique anatomical features, such as the renal artery and vein. Thus, under optimal conditions, such as maximized visible surface, image-guided kidney surgery is feasible.

The klotho-overexpressing mouse, EFmKL46, is an animal model of insulin resistance that is not hyperglycemic. In this study, the retinopathy associated with altered insulin signaling in this transgenic animal is evaluated. In four young (8-16 weeks) and 12 aged (70-80 weeks) EFmKL46 mice and age/ sex matched wild type controls, the retinal vasculature was visualized by fluorescence angiography and fundus photography. Photoreceptor function was evaluated by electroretinography (ERG). Tissue sections from post-mortem retinas were histologically examined for retinal layer anomalies and degeneration. Immunohistochemisty was used to visualize the klotho protein in mouse retinas and human retinal pigment epithelium (RPE) cells. Aged EFmKL46 mice had abnormal retinal vasculature including tortuous veins, hemorrhages, and microaneurysms. Hypo/hyperpigmentation of the retina and possible retinal scarring and exudates were observed. ERG analysis showed decreased a/b-wave amplitudes. Histological examination showed a wavy photoreceptor-RPE interface and photoreceptor degeneration which ranged from outer segment loss to the complete deterioration of the photoreceptor layer. In aged EFmKL46 mice with complete photoreceptor loss, the RPE was thickened and showed areas of proliferation. Outer retinal layers were destroyed. Antibodies indicated klotho was present throughout the retina and human RPE cells. No retinal anomalies were observed in young EFmKL46 and young and aged wild type mice. In conclusion, the nonhyperglycemic, klotho-overexpressing mouse has retinal pathologies consistent with those seen in other animal models of insulin-dependent and insulin-resistant diabetes and is a promising tool for more detailed studies of pathologies associated with insulin signaling dysfunction.

The autonomic nervous system is a regulatory structure primarily responsible for the physiologic response to environmental change, which includes the regulation of heart rate and blood pressure. Accurate assessment of autonomic function is important in the study and diagnosis of various disorders. In the research setting, autonomic sympathetic function can be assessed by directly recording the sympathetic nerve activity whereas, clinically, indirect autonomic assessment using heart rate and blood pressure variability is more practical. In this work, wavelet-based signal processing is used to improve the existing quantification schemes for both direct and indirect autonomic function. An action potential detection scheme involving the stationary wavelet transform was developed as a direct quantifier of human sympathetic nerve activity. The detection performance of this method was validated using simulated signals with varying burst rate and signal to noise ratio. Sympathetic spike detection also demonstrated a strong correlation to common integrated burst parameters in data acquired during graded upright tilt. A similar wavelet-based spike detection method was also designed for the mouse sympathetic nerve activity in order to identify differences in sympathetic function in transgenic models of autonomic disorders. A simple model was then created which used the sympathetic spike rate and the instantaneous respiration to explain the neurally-mediated low frequency oscillations and the mechanically-driven high frequency fluctuations observed in the continuous blood pressure. The model revealed a strong correlation between the low frequency fluctuations in blood pressure and spike rate at rest and during orthostatic stress. This result suggested that the low frequency blood pressure patterns could be used as an indirect estimate of sympathetic activity. Finally, a form of time varying spectral analysis capable of quantifying the power of the low and high frequency oscillations in non-stationary heart rate and blood pressure data was developed using a modified wavelet transform. This method was used to identify potential differences in the autonomic mechanisms associated with syncope alone and syncope ending in asystole, a rare stoppage of the heart, in a normal population during orthostatic stress. In summary, wavelet-based techniques are useful tools to study autonomic-cardiovascular regulation.

As the rate of obesity increases in the western world, the interest in understanding the process of maintaining healthy body weight has become an increasingly important public health priority. Because physical activity is the most variable component of energy expenditure both intra- and inter-individual, it has become a key factor in both individual weight loss prescriptions and public health recommendations. In spite of its widely recognized importance, the ability to accurately quantify patterns of physical activity has been limited by measurement technology that is often unable to render accurate predictions of energy expenditure over the course of days or weeks. One popular measurement tool for quantifying physical activity intensity is the accelerometer. Though the physical basis of the measurement would suggest that accelerometers can predict energy expenditure with a high degree of accuracy, to date, this promise has not been realized. This thesis addresses several critical gaps in our understanding of energy expenditure predictions using accelerometers. Three commercially available, single site accelerometers were coupled with seven regression equations from the literature to predict energy expenditure in a heterogeneous sample of healthy adult volunteers. We explored errors in energy expenditure prediction by both examining the accelerometer hardware as well as by proposing an analytical approach to energy expenditure prediction incorporating high frequency (32 Hz) data collection and artificial neural network modeling. Results of these experiments highlighted limitations in the single site accelerometers both in clinical data and in data collected using mechanically generated accelerations. Additionally we demonstrated improvements in energy expenditure prediction relative to single site accelerometers as well as a multi-site accelerometer array by using an artificial neural network approach for predicting energy expenditure. Results from these studies will be used to better understand the capabilities of accelerometers to assess physical activity in the field environment, which serves to improve our understanding of energy balance and obesity.

Spinal instability resulting from trauma or disease can be treated by spinal fusion, a surgical procedure that eliminates or minimizes motion at a site of degeneration in the spinal column. Autologous bone harvested from the iliac crest remains the gold standard material for use in these procedures. There are drawbacks to iliac crest harvest, however, such as limited bone availability and post-operative morbidity due to long-term discomfort at the donor site. These limitations form the basis and serve as the motivating elements in the development of synthetic alternatives. An ideal polymeric biomaterial for spinal fusion should fulfill the following criteria: capability of in situ formation, conformability to the implantation site, provision of mechanical stability, controllable degradation, osteogenicity, and biocompatibility. The objectives of this dissertation were therefore the: (1) development of a material that meets these criteria for use in spinal fusion, (2) adaptation of the material to provide sustained release of proteins, and (3) modulation of the material to provide variable release of multiple proteins. In fulfilling these objectives, we have developed and optimized a novel polymeric system for use in the spine with the additional capability of long-term sustained release of biologically active macromolecules. Our results suggest that this system may be useful as an injectable delivery system for spinal fusion applications that provides both mechanical stabilization and delivery of growth factors to stimulate new bone growth.

The objective of this study was to image tumor-targeting using a single chain fragment variable antibody to radiation-induced P-selectin in a heterotopic Lewis lung carcinoma model by near-infrared fluorescence imaging and gamma camera imaging. In our in vitro studies, we observed antibody binding to P-selectin in endothelial cells treated with radiation. In our in vivo optical imaging study, it was observed that significant tumor-specific binding was observed in irradiated tumors expressing P-selectin as compared to unirradiated tumors. Gamma camera imaging also showed successful targeting to P-selectin in irradiated tumors with tumor binding lasting for up to 10 days post-injection. Therefore, radiation-induced P-selectin is a feasible target for the tumor-specific delivery of therapeutic drugs and radionuclides in vivo.

The islets of Langerhans play a central role in maintenance of glucose homeostasis. Apoptosis of the insulin-producing beta cells of the islet leads to diabetes mellitus. The ability to non-invasively image or assess the islets of Langerhans would yield valuable insight into the progression of diabetes, guiding interventions intended to slow or halt diabetes progression and enabling assessment of islets after transplantation. The primary objective of this dissertation was to establish and validate a technique capable of non-invasively imaging the islet of Langerhans. The bulk of this work focuses on the use of bioluminescence imaging. Islets were engineered to express the luciferase optical reporter gene and applied to murine models of diabetes and transplant settings. In order to accurately quantify information from in vivo bioluminescence imaging, light-emitting standards were employed to determine sources of variance and standardize measurements. A three-dimensional bioluminescence reconstruction algorithm was characterized using these light-emitting standards and applied to bioluminescent islets. As bioluminescence imaging is limited to small animal models, clinically relevant islet imaging approaches using magnetic resonance imaging and target contrast agents were evaluated.

Current brain tumor localization methods demonstrate limited ability to discriminate between normal brain and infiltrating tumor margins, resulting in complete tumor resection in less than 20% of glioma patients. Combined fluorescence and diffuse reflectance spectroscopy can successfully discriminate between normal, tumor core, and tumor margin tissues in the brain, but fiber-optic probe-based spectroscopy produces single-point diagnostic measurements. For optical biopsy to be clinically useful in tumor resection guidance, single-point spectroscopy systems must be extended to spectral imaging which acquires spectral information at every pixel within a two-dimensional field of view, yielding spatial and spectral tissue information for a comprehensive snapshot of tissue pathology during surgery.<p>The primary goal behind each of the studies in this dissertation is to assess the capability of spectral imaging to rapidly and accurately demarcate tumor margins during surgery, requiring seamless integration of spectral imaging into the clinical environment, thorough investigation into the effects of the translation to non-contact imaging on measured fluorescence and diffuse reflectance lineshape, and high discrimination accuracy between normal tissue and tumor margins. With these mandates in mind, this dissertation describes the development and clinical testing of a combined fluorescence and diffuse reflectance spectral imaging system.<p>In vitro optical property measurements from white matter, gray matter, and glioma tissues are correlated to diffuse reflectance spectral features from probe-based spectroscopy, are used to develop gelatin-based brain tissue phantoms for system testing, and provide practical soft-tissue optical property limits for investigations into the effects of non-contact spectral imaging geometry on measured lineshape. The liquid-crystal tunable filter spectral imaging system is thoroughly characterized in terms of traditional imaging parameters (linearity, field of view, resolution, sensitivity) and functionally tested in terms of image acquisition time and its capability to spectrally discriminate between brain tissues in vitro and in vivo. The effects of a shift in excitation-collection geometry from probe-based spectroscopy to spectral imaging on measured spectral lineshape are investigated as functions of optical properties, incident excitation and emission collection angles, and the distribution of source-detector separation distances in each system geometry. Ultimately, the capability of the spectral imaging system to intra-operatively differentiate glioma core and margin tissues from normal white and gray matter is quantitatively assessed in a retrospective clinical study. Spectral features in imaging fluorescence and diffuse reflectance spectra are correlated to histopathological diagnoses of human brain tissue biopsies to determine discrimination sensitivity and specificity for brain tumor margin demarcation and subsequent utility for surgical resection guidance.