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Development of Patient-Specific Shape Memory Polymer Foams for the Treatment of Intracranial Aneurysms
No full textThe objectives of this research include: (1) designing an electrically conductive shape memory polymer (SMP) material, (2) developing a method for the systematic fabrication of SMPs with complex three-dimensional geometries based on computerized angiography tomography (CTA) of human patients, and (3) establishing translation strategies for a SMP-based endovascular device for the treatment of unruptured saccular intracranial aneurysms (ICA). We first characterized the thermomechanical properties of a porous polyurethane SMP that was infiltrated with carbon nanotubes (CNT) to induce electric conductivity in the polymeric matrix. The CNT-infiltrated SMP foams were characterized using materials science techniques that include: (i) differential scanning calorimetry (DSC) to determine the effect of CNT-infiltration on the thermal properties of the material; (ii) scanning electron microscopy (SEM) to characterize the pore morphology and interconnectivity, and (iii) uniaxial compressive testing, to characterize the effect of CNT-infiltration in the cyclic mechanical properties of the material. Then, we demonstrated the use of a CNT-infiltrated SMP foam to occlude an idealized aneurysm phantom. From these experiments, we determined that CNT-infiltrated SMP materials have the potential to be used as ICA embolic devices. However, these materials were subject to several limitations that make their translation difficult, including poor mechanical properties under cyclic compression, and a relatively high electric resistivity, that requires high currents to trigger shape recovery of the SMP. Based on the observed limitations of the CNT-infiltrated SMP material, we further performed two studies to improve the performance of our polyurethane formulation to be used as an embolic device for ICA endovascular therapy. First, we developed a method for the manufacturing of SMPs with complex 3D geometries. Due to the high degree of chemical crosslinking present in our SMP formulation, traditional 3D-printing techniques are not compatible with our material. Therefore, we developed a technique that combines leaching and 3D-printing for the fabrication of SMP foams based on CTA-informed ICA geometries. First, we fabricated polyvinyl alcohol (PVA) templates with custom pore geometries and densities. Then, we used these templates to fabricate our SMP material. By means of washing out the PVA after SMP curing, we obtained 3DSMP foams that mimicked the PVA template geometry. We also explored the effect of PVA leaching on the thermomechanical properties of the material. We found, from DSC, that the PVA leaching process induced a reduction in the glass transition temperature of the material (T_g), due to the chemical modification of the urethane groups. In addition, we found that the 3DSMP foams exhibited anisotropic mechanical properties and long-term shape recovery storage. Finally, we demonstrated the use of this manufacturing process to synthesize patient-specific 3DSMP foams. Using in vitro aneurysm models, we demonstrated that these personalized foams had the potential to provide complete ICA occlusion immediately after treatment. Building on our knowledge on the fabrication of 3DSMP foams using a leaching/3D-printing method, we aimed to induce conductivity on the 3D matrices. To do this, we performed in situ polymerization of polypyrrole (PPy), a well-described biocompatible conductive polymer, on the surface of the foams. We also modified our leaching/3D-printing method to prevent the reduction of the T_g of the material. The coating of the 3DSMP foam resulted in the induction of excellent electric conductivity on the polyurethane material. We observed that the material exhibited significantly lower resistivities than the previously developed CNT-infiltrated SMPs. This allowed the 3DSMP foams to undergo the Joule-heating process at low voltages and reach temperatures above T_g in less than 10 seconds. In addition, we developed a system to control the maximum temperature reached by the foams using pulsed electrical signals. Further, the PPy-coated 3DSMP foams underwent recovery behaviors as a response to electric stimuli. These characterizations showed the potential of the PPy-coated 3DSMP material for the development of a novel endovascular device for the treatment of unruptured saccular ICAs. In addition to the development of the material properties and functionality as an endovascular device, we also focused on planning translational research that facilitates the application of the proposed SMP-based endovascular device in the clinic. To achieve this, we first established an animal model for the testing of our embolic device in vivo prior to clinical trial studies. This animal model involves the creation of saccular aneurysms in New Zealand rabbits. Aneurysms were surgically created at the right common carotid artery by temporarily ligating the artery and then allowing an elastase solution to degrade the elastic lamina of the vascular wall. This weakening of the wall induced the bulging of the artery. In this work, we explored the stability of the aneurysms at different periods and assessed the histological structure of the aneurysms. This animal model will serve as a means to test the in vivo biocompatibility and endovascular occlusion effectiveness of our PPy-coated 3DSMP foam in the future. These future studies will be comparing the immediate and long-term occlusion effectiveness between our SMP-based device and a “gold standard” device that is currently available in the market. This comparison will demonstrate the potential superior effectiveness of our individualized treatment approach. However, selecting the gold standard as the control group is a challenging decision, due to the great diversity of modern endovascular devices for the treatment of unruptured saccular ICAs. Therefore, we performed a first-of-its-kind meta-analysis of the immediate (day 0) and long-term (post-implantation)occlusion effectiveness of modern endovascular devices. We thus performed a systematic search of studies that characterized the complete occlusion degree of ICAs of endovascular devices. Our results suggested that the most prominent endovascular devices of modern times (Guglielmi detachable coils (GDCs), flow diverters and the Woven EndoBridge) exhibit similar long-term efficacy in ICA treatment. In addition, we further showed that the immediate occlusion probability of the GDCs is the highest among the compared devices. Therefore, we selected coiling techniques as the gold standard for the in vivo assessment of endovascular embolization efficacy of our SMP-based device
Diffusional constraints implications in C-C reactions over Brønsted acid sites
No full textThe constrained pore structure and catalytic properties of zeolites can occasionally offer diffusion limitations to a molecule during the course of a chemical reaction. These constraints significantly impact the rate of condensation or cracking, either as a result of the spatial conformation of the reacting molecule inside a confined domain or the high catalytic activity of a reacting site. It is proposed an experimental approach to conveniently control the concentration of acid sites in commercial zeolite samples using the exchange property of that active proton and an alkaline atom such as sodium (Na). By combining this approach with reaction-diffusion modeling, one can measure the extent of mass-transfer limitations (MTL) in different catalytic systems and analyze the change in product selectivity or rate profile as the governing regime changes. In the case of comparing the structural differences between reactants such as acetone and cyclopentanone in restrained environments, a notable impact was observed due to the larger volume of the molecule. As the space voids increase from one constrained zeolite topology to a more accessible structure, a lower degree of mass-transfer limitations is detected. However, for the smaller reacting particle could access hindered sites as compared to the larger reactant, resulting in a higher consumption rate and notable mass-transfer limitations relative to site activity rather than spatial restraints. Instead of deactivating a site prior to the catalytic reaction, it is also investigated the in-situ addition of an inert-poison specie. While alkaline-exchange was relatively effective in quantitatively determining the extent of MTL, in-situ additions were successful in qualitatively controlling the governing regime properties and affecting the product distribution as a consequence. The structural similarities between the solvent and the titrant molecule resulted in a certain degree of desorption, which was inadequate for ascertaining the concentration of acid sites, as observed in literature.
To conveniently control the particle size through zeolite synthesis, one can also acknowledge the effect of diffusion on reaction rate. This particle presented an agglomeration of nanoaggregates over the outer surface of a big unchanged particle, in which occurred to considerably contribute towards the catalytic activity. Na-titration was able to identify mass-transfer limitations in the most active sample, but it was limited in explaining the activity reduction for the larger nanoparticle size sample.
While controlling the concentration of acid sites was proven experimentally to diminish the influence of mass-transfer limitations, the presence of mesoporosity is also another experimental route towards decrease such limitations and it is investigated here for the commercial samples of zeolite Y. The parent form of zeolite Y presented a certain degree of diffusion restraint, but as mesoporous channels were introduced, a boost in activity occurred for hydrocarbon cracking, probably through an exposure of synergistic sites. These were assumed to be either sites located in more active environments or proximate enough to contribute to a higher catalytic rate. Na-titration was adequate in identifying their contribution in activity in mesoporous samples, and decreasing the Bronsted acid density also supports the idea that proximate sites were contributing to the higher catalytic activity. By using different titrant cations, preferential titration over those synergistic sites occurred in all cases, being more effective as a bivalent cation addition. The mechanistic discussion of whether those sites favored cracking via protonation of a saturated or unsaturated hydrocarbon was performed, showing the inverse correlation between the reaction pathways rather than specific features of a catalyst only.
The results reveal the complex interplay between the reaction kinetics, diffusion limitations, and product selectivity, and provide insights into how to optimize zeolite catalysts for different applications. Overall, this work contributes to a better understanding of the fundamental mechanisms governing diffusion limitations in zeolites and provides a feasible experimental approach to more efficient design and selective processes results, being controlling the extent of mass-transfer limitations or restricting a site functioning that favors a specific reaction route
Investigation of the drivers of skin microbial diversity in six co-occurring salamander species in the presence of amphibian pathogens
Get PDFCommunities of symbiotic bacteria associated with a host, also known as microbiomes, have gained increased recognition for the myriad of key roles that they play. For example, microbiomes of the skin and gut have been linked to important host functions, such as immunity and digestion. The skin microbiome may be especially important in amphibians due to the extremely permeable nature of their skin through which they drink and respire. As a result, an imbalance in the composition of the skin microbiome, a condition known as “dysbiosis,” could have strong fitness consequences. Thus, identifying baseline skin microbial communities in amphibians may provide insight into their health and conservation needs, in addition to furthering our knowledge of microbial diversity. Several amphibian pathogens, including Batrachochytrium dendrobatidis (Bd) and viruses from the genus Ranavirus, currently decimate amphibian populations and are linked to significant changes in amphibian skin microbiomes. While an association between pathogen presence and amphibian skin microbial diversity has been demonstrated, it is not clear how widespread this pattern is or how it relates to other drivers of skin microbial diversity. For example, environmental, ecological, and genetic variables all impact the skin microbiome, making it important to quantify their contributions to microbiome structure in the presence of infection. To understand the joint influence of these factors, I used 16S sequencing to characterize the skin microbiomes of six salamander species found in Oklahoma and contrasted the effects of infection status, phylogeny, host ecology, and host environment on skin microbiomes. The results indicated that there was no phylogenetic influence on skin microbial diversity present; rather, unknown differences at the level of the salamander family were the main factors differentiating microbiome diversity, with host ecology and environment becoming more important at the level of differences among species. They also revealed a slight decrease in microbial diversity on animals that tested positive for Bd, whereas there were no microbiome differences associated with ranavirus presence. Together, these results indicate a nuanced relationship between the number and type of microbes present in the skin and the various factors influencing them. This work also provides a baseline for the skin microbiomes of six salamander species that had not been previously investigated
Panic Gardening in the End Times: An Interventional Study of Homescale Gardening on Food Security During Times of Crisis
Get PDFWhile the 20th century was characterized by decreasing food insecurity globally due to
innovations in food production and distribution, disruptions in both energy availability and
climate stability in the 21st century are presenting profound challenges to all populations
dependent on the industrial food system.
Proximity to subsistence farming has proven to be the most durable characteristic of food
security. This thesis examines the fragilities built into the industrial food system and reports on
an intervention designed to model the potential impact and challenges associated with
subsistence gardening in peri-urban settings under conditions designed to mimic a low-carbon,
climate-disrupted environment.
The study finds that time, expressed in multiple dimensions, is the greatest limiting factor
for growing enough food to meaningfully offset dependence on the industrial food system with
dietary choice ranking second. Developing a low-input method for starting seeds apart from the
gardening space is also recommended to maximize impact
Reinforcement Learning for Cognitive Phased Array Radar Surveillance
Get PDFThe proliferation of phased array radar (PAR) has significantly increased the flexibility of radar systems, making it possible to use a single radar to perform a variety of operational modes such as surveillance and tracking that each traditionally required a dedicated system.
To fully take advantage of these capabilities, algorithms must be developed to efficiently distribute the radar's finite time, energy, and processing budget between competing tasks. Although many resource management methods exist for tracking applications, it is common to use a fixed strategy (e.g., a raster scan) for the surveillance task. The resulting allocation of resources is often sub-optimal since fixed approaches do not leverage prior knowledge and thus spend a disproportionate amount of time searching regions that are unlikely to contain new targets.
This thesis presents a novel approach to more effectively utilize the radar timeline in surveillance and track initiation tasks. A variant of particle swarm optimization (PSO) is derived to estimate the density of untracked targets in the search volume, which is then used to inform the parameter selection process for each radar dwell. The resulting method, known as Surveillance PSO (SPSO), is computationally efficient and suitable for real-time implementation on a general-purpose CPU or GPU. SPSO is also highly general, making few assumptions about the properties of the target or the underlying radar system. Finally, the output of the algorithm is a constant-length tensor that can be incorporated into systems that utilize deep learning and reinforcement learning. Two cognitive agents are developed to demonstrate the utility of the SPSO algorithm. The first is a deterministic agent that directly uses the output of the SPSO algorithm to make decisions on where to steer the radar beam at each dwell. The second is reinforcement learning (RL) agent that uses a slight modification of SPSO to simultaneously steer and spoil the transmitted beam based on the current environment. The performance of each agent is evaluated in several simulated surveillance environments, where both are shown to outperform the standard raster scan approach
Managerial Perceptions and Demographic Changes Within The Higher Education Landscape at Public Four-Year Institutions
Get PDFDrawing on theory from within public policy, administration, and several types of management this project looks to explore how campus leaders at public four-year higher education institutions have responded to shifts within their environments. Populations and institutional enrollments are always changing, and this project looks at shifts that have occurred within various segments of public four-year institutions over the last two decades. Having a more holistic view of higher education data, along with in-depth case studies, the ability to better understand responses by higher education leaders becomes available
“Who asked for this?”: authenticity and race-centered corporate social responsibility
Get PDFThe purpose of this study is to conceptualize and operationalize race-centered CSR, a combination of corporate social responsibility and corporate social advocacy concerned with repairing racial relationships and inequities, and test perceptions of authenticity of race-centered CSA. Authenticity in CSR and CSA has assumed a universal consumer, however authenticity, as a cultural construct, suggests that social identity can motivate how groups of people come to understand it. As corporate social responsibility efforts increasingly center race, race itself becomes a new measure by which to understand how those efforts are seen as authentic. The study surveyed 586 Blacks and non-Blacks using a modified version of Alhouti, Johonson, and Holloway’s (2016) consumer perceptions of CSR authenticity scale, Sellers et al.’s (1997) Multidimensional Inventory of Black Identity (MIBI) scale, and adapted measures using the concepts of reconciliation and cultural commodification to conceptualize race-centered CSR and perceptions of authenticity of race-centered CSR. Two new scales were developed to measure perceptions of commodification and reconciliatory discourse as antecedents for race-centered CSR activities. Findings of this study suggests that there are universal understandings of authenticity in race-centered and of what commodification of Black culture is in the context of race-centered CSR. More importantly, the recognition of commodification of Black culture is related to perceptions of authenticity of race-centered CSR. In addition, there are subtle differences in demographic drivers for Blacks and non-blacks, particularly political ideology (conservative Blacks vs. liberal whites) and education, age, and marital status of Black respondents in perceptions of authenticity of race-centered CSR. This study contributes to The study contributes to the body of literature on critical approaches to corporate social responsibility
Quantifying the intact proteome: optimization of analytical methods for high-throughput top-down proteomics
No full textProteins play an indispensable cellular role within organisms and participate in a majority of biological functions, including enzymatic catalysis, immune reaction, and signaling. Multiple forms of a protein (i.e., proteoforms) can be generated from one single gene due to genetic variation, alternative RNA splicing, and post-translational modifications (PTMs). It has been reported that there are about ~20,000 human protein-coding genes, ~100,000 RNA splice variants, and an estimated 1 million proteoforms in complex biological systems. Different proteoforms from the same protein may have different functions and abundances; therefore, studying proteoforms is essential to understanding biological functions and the mechanisms of different biological processes.
Top-down mass spectrometry (MS)-based proteomics (TDP) techniques analyze intact proteoforms for high throughput identification, quantification, and characterization of intact proteoforms. Recent advancements in commercially available, high resolution MS instrumentation, such as improved MS resolution and scan speed, have made MS-based proteomics more accessible to the proteomics community. However, due to the extremely high proteome complexity and wide dynamic range of proteoform concentrations in complex biological samples, TDP generally suffers from low sensitivity and low proteome coverage. As such, advancements in technology to quantify and characterize intact proteoforms using top-down proteomics are imperative.
Currently, label-free quantitation is the most common quantitative approach in TDP due to the overall simplicity of application and sample handling; however, TDP suffers from run-to-run instrument variation, no multiplexing, and difficulty in implementing multidimensional (MD) separation. Application of isobaric chemical tag labeling (e.g., tandem mass tag, TMT), which is the gold-standard for bottom-up quantitation, has been limited in application to quantitative analysis of intact proteoforms to pure proteins and simple protein mixtures. Further application of isobaric chemical tag labeling to complex biological samples (e.g., cell lysate) remains challenging for three reasons: (1) protein precipitation under labeling conditions due to introduction of organic solvent; (2) production of side products including underlabeled (incompletely labeled) and overlabeled (labeling of unintended residues) species; (3) inability of MS fragmentation to simultaneously achieve adequate quantitation and identification. In this dissertation, I will present the development and optimization of sample preparation and MS methods to enable the application of TMT labeling to intact, complex biological samples.
Initially, we found that large molecular weight proteoforms tended to precipitate and “crash out” of solution under TMT labeling conditions. To minimize protein precipitation under labeling conditions, we developed a “filter-SEC” technique that couples 100 kDa MWCO filtration and size exclusion chromatography to enrich small molecular weight proteoforms (Yu D. et al. 2021). By removing larger proteoforms, we were able to accurately quantify and characterize smaller proteoforms (90% labeling efficiency for TMT-labeled E. coli cell lysate and ~86% labeling efficiency for TMT-labeled HeLa cell lysate using the optimized conditions. Finally, we evaluated the higher-energy collisional dissociation (HCD) using an Orbitrap Exploris 240 mass spectrometer for TMT-labeled complex protein mixtures. We found that high HCD energies resulted in high-intensity reporter ion peaks for accurate quantification and relatively lower HCD energies resulted in production of adequate proteoform backbone fragment ions for confident identification. However, single HCD energies were not adequate to provide accurate quantification and confident characterization simultaneously. Therefore, we evaluated stepped normalized collision energy (SNCE) schemes between 30% to 50% and found that these stepped schemes provided balance between accurate quantification and confident identification.
The innovation of an intact protein TMT labeling platform for proteoform quantitation further allowed the application of multidimensional (MD) separation to quantitative top-down proteomics to improve proteome coverage. MD separation couples two or more orthogonal separation approaches to improve separation to increase detection of low abundance proteoforms. Previously, MD separation has not been used for quantitative TDP because MD separation is not compatible with label-free quantitation due to the inability to accurately quantify proteoforms that elute in multiple first dimension fractions. We successfully integrated an automated, online 2-dimensional (2D) high-pH/low-pH reversed phase liquid chromatography (RPLC)-MS separation system with intact protein-level TMT labeling for deep proteome profiling and quantitative analysis of complex biological samples such as the HeLa proteome.
In summary, this dissertation presents the optimization of intact protein-level TMT labeling conditions to decrease the production of side products, the optimization of MS2 fragmentation energies to achieve a balance between accurate quantification and confident identification, and the coupling of automated online 2D RPLC-MS platform with protein-level TMT labeling for deep proteoform characterization and quantification in TDP. I believe that the isobaric labeling-based quantitative TDP platform demonstrated here holds great potential for the quantitative analysis of intact proteoforms in real biological samples. This will have significant impacts on many areas of proteomics research including understanding of disease state, disease progression, and biomarker discovery
Spectral Theory of Dirac Operators with Measures
Get PDFDirac operators with measures are the extension of the classical Dirac operators. We give a compatible interpretation of such a Dirac differential equation with a measure coefficient and discuss the general direct spectral theory of this kind of operators. We also discuss the relationship between a Dirac operator and a more general differential equation called a canonical system. After that, it is also discussed that de Branges spaces of a Dirac operator, which can be applied in the inverse spectral theory
Sex differences in muscle force signal complexity and variability during maximal and submaximal exercise
Get PDFSex differences have been a topic of interest in exercise physiology as of late, especially the possibility of a sex-dependent fatigue mechanism. Signal complexity has the potential to provide a better picture of fatigue by examining the behavior of a signal produced throughout a fatiguing task. Complexity measures the self-similarity and regularity of a signal and is associated with a system’s ability to respond to a change in condition. PURPOSE: To determine if there are sex differences in variability and complexity of a force signal before and/or after maximal and or/submaximal exercise. METHODS: 16 healthy untrained individuals (9 females, 7 males) completed a maximal and submaximal isometric resistance exercise test using a handmade dynamometer. The maximal exercise test consisted of a 5-minute all-out test with 30 maximal effort isometric knee extensions at a 60% duty cycle (6s contraction, 4s rest). The submaximal exercise consisted of a submaximal test performed at 50% of their maximal voluntary contraction until task failure at a 60% duty cycle. Complexity and variability measures were calculated from the first and last three contractions. Performance measures included pre and post MVC, blood lactate, rating of perceived exertion (RPE), Time-to-Exhaustion (TTE), and force decrement. RESULTS: There were significant sex differences found in complexity and performance measures. Males experienced greater fatigue and levels of complexity after maximal and submaximal exercise. CONCLUSION: Further research is needed to determine the significance and applicability of complexity measures in exercise physiology. However, it appears low complexity in females is associated with increased fatigue resistance in a healthy untrained population after maximal and submaximal isometric resistant exercise