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Design of Cardiac Valve Scaffolds from Various Polymeric Biomaterials and Assessment of Dynamic Performance
No full textCardiac valve replacement has a long history of clinical practice, yet to this day that practice is marred by suboptimal outcomes and has become a sequence of palliative measures. At the same time, the advent of tissue engineering as a concept to restore native tissue function through cell repopulation of degradable scaffolds has caused a paradigm shift in approach to cardiac valve engineering, particularly for growing valves in young patients. However, applying tissue engineering principles to the cardiac valves has not been straightforward. From the earliest attempts until even recent clinical trials of these tissue engineered heart valves, a great deal has remained unknown, such as biological mechanisms of cell infiltration and neotissue formation as well as optimal valve design considerations for recreating native-like mechanical deformation and dynamic functional performance.
Therefore, it was the objective of this dissertation to further elucidate some of these unknowns, namely the material properties and geometry and their influence over structural and fluid mechanics. Additionally, comparing the functional performance of valve scaffolds sized for both adults and children was a crucial component. The experimental efforts reported herein identified two key design parameters, namely material stiffness and valve geometry, that could be modified toward optimization of valve scaffolds. Among the two primary variables tested here, the geometric configuration played a relatively more significant role than material stiffness in determining valve function and mechanical properties. Specifically, while valve performance generally diminished with increasing stiffness, extending the free edge length proved to be a significantly greater modification, contributing to a significant reduction in strain concentrations throughout the leaflet surface as well as reduced fluid jet velocity. Additionally, the electrospinning process used to fabricate valve scaffolds was tuned to allow for tightly controlled polymer deposition patterns in both adult- and pediatric-scale scaffolds. Future study may use this research as groundwork for iteration on valve design coupling experimental validation to computational modeling, as well as optimizing additional design features to improve both mechanical and host responses to degradable valve scaffolds on the road towards clinical translation
Unraveling Ocular Tissue Biomechanics: Characterizing Collagen Microstructural Features and Introducing Direct Fiber Modeling
No full textGlaucoma, a progressive optic neuropathy, is primarily associated with elevated intraocular pressure (IOP) and mechanical insult on ocular tissues. The optic nerve head (ONH) and lamina cribrosa (LC) are particularly vulnerable to early nerve damage, while the sclera surrounding the ONH, provides essential mechanical support and stability. Understanding the biomechanics of these ocular structures is crucial for unraveling the mechanisms of glaucoma.
The biomechanics of ONH, LC and sclera are intricately connected to their collagen microstructure, necessitating a comprehensive understanding of tissue microstructures and their associated biomechanical properties. However, despite extensive work, several microstructural characteristics have not been considered carefully, largely due to limitations in visualization tools. Furthermore, current modeling approaches in ocular biomechanics often neglect potentially critical fiber characteristics, limiting their ability to describe tissue structure and mechanics, particularly at fiber-level scales.
Using advanced imaging techniques like polarized light microscopy, this dissertation characterizes two critical microstructural features that have been ignored: LC insertions and the in-depth collagen fiber organization of corneoscleral shell. We characterized the spatial variations of LC insertions and variations of insertions among species. The discrete insertions of the LC beam indicate that the interaction between LC and the surrounding load-bearing tissue is discontinuous, leading to localized force concentrations. Diverse insertion shapes suggest varying robustness in the LC periphery, potentially influencing susceptibility to glaucomatous damage. We also present a detailed analysis of the in-depth organization of collagen fibers within the corneoscleral shell for a better characterization of the complex three-dimensional collagen architecture. This, in turn, will enhance the understanding of the out-of-plane tissue mechanical properties.
Leveraging detailed information available from the imaging, this project proposes and validates a novel direct fiber modeling approach that represents fibrous microstructure, accounting for fiber interweaving, interactions, and specimen-specific collagen architecture. The proposed model replicates anisotropic mechanical behavior observed in different loading protocols and across different samples, providing unprecedented details on fiber-level tissue behavior.
In conclusion, this dissertation uncovers crucial microstructural features of ocular tissue and introduces an innovative direct fiber modeling technique. The findings contribute to a deeper understanding of ocular tissue microstructure and biomechanics, advancing our knowledge of glaucoma pathogenesis
Pancreatic Islet Microphysiology System for Disease Modeling of Type 2 Diabetes
No full textDiabetes has become an increasingly prominent global issue afflicting 10% of world’s population where type 2 diabetes (T2D) comprises the majority of those diagnosed. T2D correlates with a toxic bioenvironment that leads to the body’s inability to properly self-regulate blood glucose due to the dysfunction of insulin producing pancreatic islets. While the outcome of T2D is well recognized, the pathogenesis of the disease still requires greater understanding with most studied mechanisms having a non-human basis. Additionally, current disease models fail to fully replicate disease conditions for drug testing leading to only 10% success in clinical trials. To bridge the gap and more accurately replicate human disease, microphysiological systems (MPS) have risen as a viable alternative since they combine microfluidics and tissue engineering to mimic the in vivo micro-environment.
This dissertation focuses on the development of an islet-MPS that utilizes both primary and stem cell-derive tissue to simulate the pathogenesis and drug testing for T2D. In this pursuit, we developed the pancreatic islet (PANIS) system that was able to sustain a healthy islet environment with glucose sensitive insulin secretion from both primary and stem cell-derived islets for more than two weeks. Disease induction was tested by subjecting the primary islet PANIS to toxic conditions correlated with T2D, such as hyperglycemia and/or high free fatty acids (lipotoxicity). The effects of these combinations were studied thoroughly using viability and functionality assays along with RNA sequencing to determine how each toxic factor affected islets and what toxic condition would most closely replicate T2D. This toxic conditioned islet MPS was able to test drug efficacy with dose dependent trials using the anti-oxidant drug, Resveratrol. Additionally, innate immune cell interactions were studied by co-culturing the primary and stem cell-derived islets with neutrophils while simulating disease conditions. The result of this dissertation ultimately provides a robust islet MPS that can be used to model islet-specific disease induction and drug treatment with the capabilities for personalized medicine using human stem cells
From Well Log to Formation Model: A Novel Laboratory Calibrated Methodology with Demonstration
No full textThis work demonstrates how the characterization and modeling of both elastic and creep properties are essential to describe zones in layered rock formations as either low-stress targets for stimulation or high-stress barriers to fracture growth. Prediction of fracture height is critical for designing stimulation operations in oil and gas wells. Ideally, fractures are placed in target zones which will produce hydrocarbons and should not propagate into zones expected to be unproductive or to produce unwanted fluids such as water which in turn must be treated and/or disposed. The essential task in designing stimulation plans is predicting which zones have low horizontal stresses and which will be high-stress barriers to fracture growth. Despite this importance, there are gaps in current knowledge and a complete workflow from laboratory characterization to a finite element model which includes time dependent rock deformation is required.
While the research and methodology presented here also have application to CO2 or hydrogen storage, wastewater injection, and geothermal applications, the focus will be on hydrocarbon extraction. This thesis presents the results of a characterization-to-prediction workflow for the Caney shale, which is an emerging hydrocarbon resource in Oklahoma, USA. It begins with an investigation to enable critical evaluation of the Caney zonation into nominally “brittle” and “ductile” zones based on properties observed from well logs. It shows none of the zones are consistently “brittle” or “ductile” mechanical behavior based on the variety of definitions of these terms. However, the nominally ductile zones are weaker and more prone to creep.
A laboratory investigation of samples including strength, elastic, and creep properties, is then used in a finite element model of stress evolution. The model includes both elastic deformation and viscoplastic creep. Results predict the least creep-prone layers to have the lowest horizontal stresses, therefore comprising hydraulic fracturing targets. The most creep-prone layers attain a horizontal stress similar to the vertical stress and therefore are predicted to be high stress barriers to hydraulic fracture stimulation. In addition to defining stimulation target intervals, the model shows how as tectonic strain rate increases, there is a transition from creep-dominated stresses to stresses dominated by elasticity
Demographic Determinants of Perceived Health Risks from Pollution in the Wake of Petrochemical Industry Expansion in Beaver County, PA
No full textMany view fossil fuel reliance and petrochemical industrialization as a public health concern while others view it as an economic necessity. However, these perceptions can change over time after industrial impacts have manifested. With the recent development of the Shell Polymers Monaca plant in Beaver County, Pennsylvania, my internship project objective was to collect and analyze baseline data regarding residents’ perceptions on health prior to and soon after full operational activities began at the plant. A Qualtrics cross-sectional community health survey was distributed to adult residents of Beaver County from July 2022- August 2023. Participants were recruited both through Pitt+Me and through the dissemination of fliers by study staff and members of a community advisory board. The survey gathered information related to demographics, self-reported health habits, perceived community and personal health, and attitudes towards environmental health. To measure perceptions, participants responded to a series of statements using a 5-point Likert scale. Descriptive statistics were generated using Qualtrics XM and univariate and multivariate linear regression analyses were performed using R version 4.2.3. The survey was comprised of 436 adult residents of Beaver County zip-code. Approximately 36% and 25% of survey takers indicated that their health had been harmed by air pollution or unsafe drinking water, respectively. Results from the regression analysis showed that perceived health and certain health habits were statistically significant predictors for agreeing or disagreeing with the statements “My health has been harmed by unsafe drinking water” and “My health has been harmed by air pollution”. The baseline survey data illustrates that there is a high prevalence of concern about current and future exposure to pollution in Beaver County. A follow-up survey will be redistributed to participants a year after the initial survey completion date to determine if there are changes in perceptions since the plant began operations. These findings can assist community leaders with addressing and advocating for participants’ expressed issues regarding exposure to air and water pollution – an issue of great public health importance
Attitudes Towards Anal Cancer and Screening Among People Living With HIV(PLWH) in Puerto Rico and Their Association with Educational Attainment
No full textBackground: Anal cancer is a critical public health issue since its incidence has been rising in the past years. Lack of knowledge poses challenges in prevention, screening methods, and treatment, which warrants immediate intervention and early detection efforts. While persons living with HIV are at increased risk of anal cancer, limited research exists among Hispanic persons living with HIV with respect to this malignancy and use of screening methods. A lack of awareness
with anal pap tests, an essential screening tool for the early detection of anal cancer, hinders screening efforts leading to a higher burden of disease in this high-risk population; a health disparity issue that needs further research.
Methods: Between November 2020 to December 2021, 212 PLWH living in Puerto Rico completed a telephone-based interview assessing medical, sexual history, socio-demographic, lifestyle variables, alongside attitudes and knowledge pertaining to anal cancer screening. Descriptive statistics and multivariate regression were performed using SAS and STATA.
Results: Overall, 67.5% participants were male and aged ≥ 50 years. Concerning anal cancer, 81.3% expressed worry about developing anal cancer, 96.7% were willing to have an anal pap test in the future, and 97.2% wanted to learn more about the disease. Moreover, 75.9% had previously shown interest in getting an anal pap test, while 65.9% mentioned feeling nervous about their test results. After adjusting for age and sex, PLWH with a high school education or less were more likely to perceive anal cancer as a hopeless disease (OR: 2.3, 95% CI: 1.18-4.32), early detection methods as very uncomfortable (OR: 2.9, 95% CI: 1.46-5.70) and the impact of anal cancer on life as minimal (OR: 2.5, 95% CI: 1.18-5.50) as compared to individuals with higher education.
Conclusion: Those in the lower educational attainment category had the most negative attitudes toward anal cancer and current screening methods. This work underscores the public health importance of the urgent need for increased education and awareness about anal cancer screening in PLWH, where stigma is high, particularly among individuals from disadvantaged backgrounds
Data associated with publication: "Separating geometric and diffusive contributions to the surface nucleation of dislocations in nanoparticles" by R. Ding, S. Azadehranjbar, I.M. Padilla Espinosa, A. Martini, and T.D.B. Jacobs, published in ACS Nano, 2024
No full textData associated with publication: "Separating geometric and diffusive contributions to the surface nucleation of dislocations in nanoparticles" by R. Ding, S. Azadehranjbar, I.M. Padilla Espinosa, A. Martini, and T.D.B. Jacobs, published in ACS Nano, 202
High-Temperature Oxidation and Fatigue Performance of Alloy 625: Effect of Alloy Manufacturing Process
No full textAlloy 625 is a nickel-based superalloy which is strengthened mainly by solid-solution hardening. Multiple efforts have been made to fabricate complex parts by additive manufacturing (AM), taking advantage of the freedom of design, sustainability benefits, and the manufacture of hard-to-machine alloys. However, one of the major drawbacks of the AM implementation for components with both high mechanical and chemical requirements is the lack of full understanding of the processing-structure-properties relationships.
Alloy 625 applications at elevated temperatures required good mechanical properties combined with good corrosion and oxidation resistance. The latter relies on the protectiveness provided by the thermal growth chromia scale. Previous studies have assessed mechanical and chemical performance, finding high variability and inconsistent results within the alloy specifications. Furthermore, previous assessments of these properties have been conducted separately without considering the potential impact of oxidation on mechanical performance.
This study aims to elucidate the impact of the microstructural variables stemming from laser additive manufacturing processes on the high-temperature oxidation behavior and fatigue performance of alloy 625. Two laser-assisted AM processes were studied: laser powder bed fusion (LPBF) and direct energy deposition (DED), and wrought and cast alloy were used as a reference. During the early stages of oxidation, it has been observed that the extent of Nb and Mo segregation affects the formation of transient products, which in turn delays the development of a protective chromia scale. In the steady-state oxidation regime, it has been noted that the AM samples show consistently faster oxidation kinetics. Additionally, the AM samples also exhibit more damaged subsurface and chromia scale, characterized by a larger oxide scale decohesion, non-planar interface, internal voids, and severe intergranular oxidation. The excess of voids formation in oxidized AM samples is attributed to the higher interstitial oxygen gain during the alloy manufacturing processes. The combined effect of these defects (i.e., interfacial voids, delta-precipitates, internal oxidation) accelerates the alloy degradation during high cycle fatigue, ultimately resulting in a significant reduction in fatigue life compared to the wrought sample. The most detrimental factor for fatigue performance is severe intergranular oxidation
Foreword – The Network Is the Message
No full textA new service model has emerged for librarians in response to the changes and challenges of the network society and participatory culture of the 21st century. Internet connectivity and electronic communities have blurred boundaries between consumers and producers, learners and teachers, work and play, school and community. Collective endeavours have replaced solo efforts, putting communication, networks and relationships at the heart of professional practice and making collaboration, teamwork and partnership the standard mode of operation for school librarians, not a strategic option for consideration in particular circumstances. Practitioners are broadening their networks beyond teachers and librarians to engage with students and their families, as well as teaming up with other specialists and community actors. They are also deepening their connections with contacts, which has often meant major upskilling to develop the technical and behavioural abilities needed for building and leading teams, communicating in multiple modes, and managing change and conflict
Data Compression, Uncertainty Quantification, and Prediction Using Low-Rank Approximation
No full textDimension reduction techniques are valuable for both data-rich and data-poor problems. For applications involving massive high-dimensional data, dimension reduction can be utilized for data compression and data-driven discovery. In the data-poor regime, low-rank subspaces enable field reconstruction with only a few sparse measurements. Moreover, reduced-order modeling effectively propagates parametric uncertainty in high-dimensional partial differential equations. This work aims to develop dimension reduction techniques based on spatiotemporal subspaces for applications across the data-availability spectrum as well as performing uncertainty quantification in high-dimensional dynamical systems.
First, we develop a low-rank approximation that compresses the size of transient simulation data in real-time, which helps with storage and input/output limitations. These limitations also restrict data analysis and visualization in large-scale simulations. To address this issue, we present an in-situ dimension reduction technique that decomposes the streaming data into a set of time-dependent bases and a core tensor in real-time. This method is adaptive and controls the compression error through the addition or removal of modes.
We then develop dimension-reduction methodologies for prediction in data-poor regimes. While it is possible to predict blood flow using machine learning models, clinical measurements, such as Transcranial Doppler ultrasound, may be insufficient or too low-resolution for the training process. Therefore, developing a computational model that provides predictions based on sparse data is crucial. To this end, we present a physics-informed regression framework based on Gaussian process regression to predict blood flow properties using very few sparse measurements.
Lastly, we extend the application of low-rank approximation to uncertainty quantification in blood flow simulations. In clinical settings, measurements are often intrusive and inherently uncertain. Numerical simulations could aid in developing non-invasive assessments. However, physiological variability introduces uncertainties in simulation parameters, necessitating a large number of computationally expensive simulations. To address these challenges, we explore implementing a low-rank approximation approach that reduces computational costs while maintaining accuracy