Electrostatic complexation of a cationic MAPKAP kinase 2 inhibitory (MK2i) peptide with the anionic, pH-responsive polymer poly(propylacrylic acid) (PPAA) yields MK2i nano-polyplexes (MK2i-NPs) that significantly increase peptide uptake and intracellular retention. This study focused on elucidating the mechanism of MK2i-NP cellular uptake and intracellular trafficking in vascular smooth muscle cells. Small molecule inhibition of various endocytic pathways showed that MK2i-NP cellular uptake involves both macropinocytosis and clathrin mediated endocytosis, whereas the free peptide utilizes clathrin mediated endocytosis alone for cell entry. Scanning electron microscopy studies revealed that MK2i-NPs, but not free MK2i peptide, induce cellular membrane ruffling consistent with macropinocytosis. TEM confirmed that MK2i-NPs induce macropinosome formation and achieve MK2i endo-lysosomal escape and cytosolic delivery. Finally, a novel technique based on recruitment of Galectin-8-YFP was developed and utilized to demonstrate that MK2i-NPs cause endosomal disruption within 30 minutes of uptake. These new insights on the relationship between NP physicochemical properties and cellular uptake and trafficking can potentially be applied to further optimize the MK2i-NP system and more broadly toward the rational engineering of nano-scale constructs for the intracellular delivery of biologic drugs.

Background Effective medical software is designed to fit the needs of the end users, translating their work into action. User-centered design seeks to involve users at all stages of the design process, but the process itself can be tedious, leading to variable degrees of implementation amongst vendors. This research seeks to create a new method of involving multiple end users remotely in the user-centered design process in order to establish the features and design required for clinicians need to perform effectively. Objectives The objectives of this research are to summarize currently identified necessary pediatric-specific EHR functionalities and create an online software platform to delineate further needs and functionalities, contributing to remote user-centered design of electronic medical record software. Methods We created Vanderbilt Active Interface Design (VandAID), a novel web-based software platform for crowdsourcing user interface design. The platform provides immediate real-time feedback on user interface design and layout decisions using example patient scenarios. The scenarios can pull information from a variety of sources using standards such as a Fast Health Interoperability Resource (FHIR). The design platform allows the selected options to be sent to a REDCap project for statistical analysis or viewed directly in the VandAID platform. We performed a randomized controlled trial to test the usability and utility of this software platform for the design of a neonatal handoff tool. Conclusions This research advances scientific approaches to user-centered design of health information technology by creating a means of collecting remote feedback from multiple users. Results from the randomized controlled trial in the first use case demonstrate this software platform to be a highly usable and effective means of performing cooperative user-centered design.

Electronic health records (EHRs) are rich data sources that can be analyzed to discover new, clinically relevant patterns of disease manifestations. However, sparsity, irregularity, and asynchrony in health records pose challenges for their use in such discovery tasks, as standard statistical and machine learning techniques possess limited ability to handle these complications. Abstracting the clinical data into models and then using elements of those models as input to statistical and machine learning algorithms is one approach to overcoming these challenges. This dissertation provides insight into the use of different models for this purpose. First, I examine the effect of model complexity on algorithm performance. Specifically, I examine how well different models capture the low-specificity information distributed throughout electronic health data. For several predictive algorithms, low-complexity models turn out to be nearly as powerful and much less costly as high-complexity models. I then explore the use of continuous longitudinal models of laboratory results and diagnosis billing codes to discover clinically relevant patterns between and among these data. I look for associations between clusters of specific laboratory values and single billing codes, and identify known associations as well as others that are consistent with current medical knowledge but not expected a priori. Finally, I use the same longitudinal abstraction models as inputs into more complex probabilistic models that adjust for indirect associations, and find that diagnosis codes can be used to predict the laboratory status of a patient.

Photothermal OCT (PT-OCT) is an emerging molecular imaging technique that occupies a spatial imaging regime between microscopy and whole body imaging. PT-OCT has been demonstrated in vitro, ex vivo, and in vivo on multiple contrast agents such as gold nanoparticles and indocyanine green. PT-OCT would benefit from a theoretical model to optimize imaging parameters and test image processing algorithm. Past models have focused on individual components of the PT-OCT signal, but a comprehensive model still had to be assembled. We propose the first PT-OCT model to replicate an A-scan in homogeneous and layered samples. Our predictions were validated experimentally in silicone phantoms. We also propose the PT-CLEAN algorithm to reduce phase-accumulation and shadowing, two artefacts found in PT-OCT images and demonstrate this algorithm on phantom and in vivo images.

Simultaneous multislice (SMS) imaging is a scan acceleration method where mul- tiple slices are simultaneously excited using a multiband pulse and the aliased slice images are separated in reconstruction using the receive coils sensitivity maps. At high main field strengths, SMS brain imaging suffers from artifacts caused by non- uniform and subject-dependent transmit RF fields and large magnetic susceptibility differences near air-tissue interfaces such as the frontal sinus and the middle ear. Another significant engineering challenge is the increase in peak power of multiband pulses with the number of excited slices. In this research work, we propose novel radiofrequency pulses and pulse sequences to address these SMS imaging problems. Low peak power multiband spokes excitation pulses are proposed to mitigate the image shading artifacts caused by inhomogeneous transmit RF field in multiple si- multaneously excited slices. Results from simulations and in vivo experiments at 7 T demonstrate that images excited using multiband spokes pulses have reduced center brightening artifact than conventional multiband pulses. We propose a novel pulse sequence called multispectral z-shim to reduce the through-plane signal loss artifact in structural and functional MR imaging. In vivo experiments show that the multispectral z-shim sequence recovers signal in regions of susceptibility difference in multiple brain regions while maintaining signal elsewhere. To reduce the peak power of conventional pulses, we present a method to design root-flipped multiband pulses. Simulations and experiments demonstrate that for a fixed peak amplitude, the root-flipped pulses excite the desired slices with a pulse duration lower than that of pulses proposed earlier. The work presented in this dissertation will improve high field SMS imaging research in areas such as functional MRI, susceptibility-weighted imaging and diffusion-weighted imaging.

Sensitive and specific noninvasive in vivo imaging of contrast agents and endogenous molecules can supply molecular and functional information in animal models, providing essential insight into mechanisms of disease formation and progression, drug delivery, and treatment response. In cancer in particular, high resolution imaging is essential for capturing spatial heterogeneities in molecular expression and the tumor microenvironment that cause significant barriers to treatment efficacy and drug delivery. Optical coherence tomography (OCT) fills the niche of cellular-level resolution and penetration depths in tissue that exceed those obtained with microscopy, an attractive regime for imaging mouse models of cancer. In this dissertation, photothermal OCT (PTOCT), a functional extension of OCT, was developed for in vivo imaging of a variety of contrast agents and drug delivery vectors in live animals. The PTOCT signal was thoroughly characterized in phantoms and compared to theory, followed by a demonstration of picomolar sensitivity to gold nanorod contrast agents. Gold nanorods at physiologically relevant concentrations were then identified from within a live mouse at depths exceeding the standard limits of high resolution optical microscopy. Then, heterogeneities in gold nanorod delivery to tumors were imaged in the context of tissue and vessel morphology, demonstrating the utility of PTOCT as part of a powerful multimodality imaging platform for the development of nanomedicines and drug delivery technologies. The uptake of gold nanorods into mouse mammary tumors were tracked in three dimensions over 24 hours, and the specificity of the PTOCT signal was verified using multiphoton microscopy. Finally, photothermal optical lock-in optical coherence tomography (poli-OCT) was used to increase system throughput and allow for real time photothermal imaging. In vivo poli-OCT of indocyanine green identified lymphatic vessels in a mouse ear, and also identified picomolar concentrations of gold nanorods in subcutaneous injections at frame rates ten times faster than previously reported. Overall, the development of in vivo PTOCT combined with existing morphological and hemodynamic imaging capabilities of OCT will enable more comprehensive studies of drug delivery and molecular expression in mouse models of disease, particularly cancer.

No description available.

The objective of this dissertation was to develop an experimental approach and supporting software for performing and interpreting the results of micoarray-based experiments, as well as apply this approach to an experimental model of angiogenesis and blood vessel development. When this project was initiated microarray technology was in its infancy and the standard experimental design was to hybridize two samples against each other and report intensity ratios that were greater than two-fold. In order to study the changes in gene expression that occur over the course of the vascularization process, it became clear that a new approach to microarray experimental design and analysis was required. It was also clear that most researchers were ill-equipped to process and interpret the tens of thousands of data points generated by microarray experiments. To address these needs, a software package called CARMA (Computational Analysis of Replicated Measurements for Arrays) was developed to perform an analysis of variance (ANOVA) on microarray experiments that incorporate replicated measurements. Utilizing replicated measurement-based designs makes it possible to incorporate multiple samples into the experimental design and calculate both the magnitude and the statistical significance of the differences in gene expression between samples. Software was also developed to implement and compare different algorithms and distance metrics for performing hierarchical clustering. Hierarchical clustering groups genes together based on the similarity of their expression profiles, and is used to reduce the complexity of a microarray dataset and identify genes that may be involved in the same or related processes or under similar types of transcriptional control. Utilizing simulated datasets containing known clusters of genes, the ability of each each algorithm/distance metric combination to recover the original clusters was evaluated. Lastly, both CARMA and hierarchical clustering were utilized to analyze changes in gene expression during the process of vascularization in an experimental model of angiogenesis and blood vessel maturation. Based on high-level patterns of gene expression and morphological measurements obtained using this model, a multi-phase model of angiogenesis-based vascularization is presented consisting of an initial angiogenic phase, followed by a maturation and network remodeling phase.

Colorectal cancer (CRC) is the third leading cause of cancer related deaths. Rodent models of CRC are useful for evaluating diagnostic tools, therapeutics, and disease progression; however, an appropriate imaging tool is needed. Optical coherence tomography (OCT) is a non-destructive imaging modality readily packaged into small diameter endoscopes. Using a near- infrared light source, structural images are generated from index of refraction mismatches with resolutions of 2-15 mm at imaging depths of up to 1.3 mm. In contrast, laser-induced fluorescence (LIF) spectroscopy provides information about biochemical composition, exciting tissues with ultraviolet to green wavelengths of light to measure fluorescence emission from endogenous fluorophores such as NADH, collagen, and porphyrin.We apply OCT and LIF to mouse models of CRC, beginning with a comprehensive ex-vivo evaluation of normal mouse gastrointestinal (GI) tract in various strains and ages and secondarily sampled colorectal neoplasia and inflammatory bowel disease (IBD) using a combined in-air OCT/LIF system. A set of characteristic features of OCT images were developed for normal esophagus, small intestine, and colon; preliminary image feature criteria were also developed for colorectal neoplasia and IBD. LIF characterized the endogenous fluorescence of mouse GI tract, with spectral features corresponding to collagen, NADH, and hemoglobin. In the IBD sample, LIF emission displayed potentially diagnostic peaks at 635 and 670 nm, consistent with increased porphyrin production by bacteria associated with IBD.Next, endoscopic OCT/LIF was evaluated in an in-vivo serial study using a prototype 2 mm diameter endoscope to image the lower colon of ApcMin and control mice. Adenoma development over OCT imaging timepoints was characterized as a progressive mucosal thickening to frank mass formation. LIF spectral comparisons revealed decreased 405 nm intensity and the presence of a peak at 680 nm over adenoma.In a final study, ultrahigh resolution OCT (UHR OCT) was used to serially image the lower colon of azoxymethane treated A/J mice to monitor CRC progression and determine OCT's capability of identifying early disease. A panel of blinded mouse colon pathology experts assigned a diagnosis based on the OCT images, which was then compared to a histological diagnosis assigned by a blinded pathologist. At the final imaging timepoint, 95% of adenomas and 23% of gastrointestinal intraepithelial neoplasia (GIN, 38% protruding GIN and 9% non-protruding GIN) were correctly diagnosed. The panel identified 68% of disease foci (95% adenoma, 76% protruding GIN, and 13% non-protruding GIN). Over the OCT imaging timepoints, disease progression followed a typical succession, with normal or GIN preceding adenoma. Endoscopic UHR OCT enabled accurate diagnosis of adenomas, identification of protruding GIN, and non-destructive visualization of CRC progression, providing a tool for cancer research in animal models.

The apparent diffusion coefficient (ADC) is a quantitative measure of water diffusion in tissue which is sensitive to the microstructural features of brain tissue and can be measured non-invasively with diffusion-weighted MRI (DWMRI). Within minutes after the onset of ischemic stroke, the ADC of water decreases 30-50% within the affected tissue. Although this was initially discovered nearly two decades ago, there is no consensus on the biophysical mechanisms responsible for the drop in ADC after ischemia. This dissertation investigates the biophysical mechanisms which determine the ADC through mathematical models of water diffusion in tissue as well as experiments in hollow fiber bioreactor (HFBR) cell cultures.The mathematical model of water diffusion in tissue predicts that the biophysical mechanisms which affect the ADC are diffusion time dependent. At short diffusion times, the ADC is sensitive to the intrinsic diffusivity of intracellular water, while at long diffusion times, the ADC is sensitive to changes in the intracellular volume fraction. Furthermore, the ADC changes associated with ischemia can be account for completely by a change in the intracellular cell volume fraction when the intracellular T2 is allowed to be lower than the extracellular T2.A unique feature of the HFBR bioreactor cell culture system is that it allows the diffusive properties of intracellular water to be investigated individually. The change after ischemia in the ADC measured from intracellular water (iADC) is dependent upon the diffusion time used to collect iADC measurements. At short diffusion times, the iADC decreases after ischemia, which is likely due to a decrease in the energy dependent movement of water within the cell. At long diffusion times, the iADC increases after ischemia, which is related to cell swelling. The results from the HFBR experiments are consistent with the mathematical model and provide a clear picture of the biophysical mechanisms important to measurements of water diffusion in living and ischemic tissue with DWMRI.