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TRPV4 MUTATIONS CAUSE BLOOD-CNS BARRIER INTEGRITY BREAKDOWN IN MOTOR NEURON DISEASE
No full textDisruption of blood-brain (BBB) and blood-spinal cord (BSCB) barriers, is an early driver of neurodegenerative disease, yet the mechanisms underlying their impairment remain poorly understood. Neurovascular endothelial cells (NVECs), joined by tight and adherens junctions, form the barrier’s first line of defense. The mechanosensitive ion channel transient receptor vanilloid 4 (TRPV4) is enriched in NVECs and gain-of-function TRPV4 mutations cause motor neuron disease. However, their impact on CNS vascular integrity is unknown. This thesis investigates how TRPV4 mutations, particularly R269C, impair NVEC barrier function. Trpv4R269C/R269C mice developed forelimb weakness, motor neuron degeneration, and early lethality. Cultured NVECs isolated from these mice exhibited increased calcium influx and barrier breakdown following TRPV4 activation. In vivo, focal BSCB leak in the cervical spinal cord preceded motor neuron loss and was reversed by endothelial-specific TRPV4 deletion or pharmacologic inhibition. To characterize the cellular basis of this dysfunction, we modeled the human BBB using isogenic iPSC-derived brain microvascular endothelial-like cells (iBMECs). Mutant TRPV4 iBMECs showed loss of laminin-dependent regulation and exaggerated calcium influx in response to a TRPV4 agonist and shear stress. Flow triggered tight junction disorganization in mutant cells, with morphological ZO-1 changes observed specifically in cells with high calcium influx. These findings suggest that mutant TRPV4 drives focal barrier vulnerability downstream of aberrant calcium signaling. Together, this work identifies TRPV4 as a NVEC mechanosensor and a regulator of CNS barrier stability. It provides insight into how TRPV4 gain-of-function mutations trigger vascular dysfunction and supports therapeutic targeting of TRPV4 in neurodegenerative diseases
Autonomous Neuromorphic Computing: Information Flow and Design of Polymer-Linked Nanoparticle Networks
Get PDFThis dissertation explores a framework for developing polymer-linked nanoparticle (PLNP) networks as novel autonomous computing neuromorphic materials (ACNMs) through a multiscale approach. We address fundamental limitations of conventional computing architectures, where the von Neumann bottleneck combined with silicon’s physical constraints necessitate radically different approaches for the development of next-generation computing systems. Drawing inspiration from the brain’s remarkable computational efficiency, this work investigates PLNP networks across three distinct scales. At the nanoscale, all-atom (AA) molecular dynamics (MD) simulations reveal thermal conductance across different polymers connecting two gold nanoparticles (AuNPs) and its dependance on the structure of the polymer, with conjugated polymers demonstrating superior conductivity properties that scale additively with multiple linking chains. At the mesoscale, dissipative particle dynamics (DPD) simulations demonstrate how temperature and electric fields shape network topology,
with increasing the length of a polymer chain significantly enhancing nearest-neighbor connectivity. At the scale of an algorithmic framework, mathematical modeling of small networks identifies conditions for generating stable limit cycles (LCs), the differences between which could enable dynamic information storage, with networks showing robustness to structural perturbations. Together, these findings establish a foundational framework for developing tunable PLNP networks as materials that could inherently process and store information without conventional electronic components, offering a promising direction for brain-inspired computing paradigms
IMPROVING DEPARTMENT OF DEFENSE FINANCIAL EXECUTION BENCHMARKS FOR UNIVERSITY-LED BASIC RESEARCH PROGRAMS
Get PDFThe Department of Defense (DoD) is the largest federal sponsor of research and development. Each year, the DoD funds over $100 billion in research, development, test, and engineering (RDT&E) across eight budget activities codes. These activity codes provide a budget framework to support science and technology from basic research through system demonstration.
Despite the major differences in the RDT&E activities and performers across these budget activities, the DoD utilizes a single set of financial benchmarks for all programs. As a result, universities, DoD laboratories, and major defense contractors are held to the same financial execution. For university-led basic research, these benchmarks are unrealistic and have resulted in programs having their budgets reduced or even terminated in some cases.
This capstone investigates the inadequacies of existing DoD financial execution benchmarks as applied to basic research programs awarded to universities. Through a mixed-method approach of analyzing historical DoD appropriations and expenditure trends, literature review, and a real-world case study of a university-led DoD cooperative agreement, this study identifies key issues with the current application of these financial benchmarks. Findings reveal that delayed appropriations and awards, misaligned operational schedules, and complex management of cost-reimbursable agreements directly impede universities’ ability to meet existing benchmarks.
The capstone offers five recommendations to improve DoD financial execution benchmarks for university-led basic research programs. These include developing distinct benchmarks tailored to university-based research, integrating the timing of federal appropriations, aligning award schedules with academic calendars, reforming the application of financial execution metrics, and adopting a model to better support actual expenditure trends. Ultimately, this capstone advocates the need for an improved financial execution benchmarking system for university basic research that maintains fiscal accountability while accommodating the unique challenges of university research environments and protecting basic research
No Race, No Problem: Examining the Correlates and Consequences of Critical Race Theory Bans in K-12 Education
Get PDFSocial conflicts often come to a head in public schools. Critical race theory (CRT) has been the topic of one such conflict in recent years. Although CRT is a theoretical legal framework not taught in K-12 schools, it has been weaponized as a catchall term for curriculum, professional development, and district strategic planning related to race, racism, diversity, equity, and inclusion. As of Fall 2023, 17 states and at least 60 school districts took action to restrict or ban curriculum and discussions related to race/racism in public schools under the guise of protecting students from racial shame and CRT. Given the recency of this trend, the research on CRT bans is limited. Drawing on multiple administrative data sources, this dissertation takes a multifaceted approach to explore different aspects of CRT bans. In the first study, I use document analysis to explore patterns in language and policy justifications in a sample of district- and state-level anti-CRT policy documents. I find that document language varies by governance level and legislative weight. Additionally, anti-CRT documents often use color-evasive racist logics and their conceptions of American values to justify restricting content on topics related to race and racism. The second study uses mapping and regression analysis to examine contextual factors associated with district-level CRT bans. My findings suggest that ban adoption is more likely among school districts in Republican-leaning counties that have become less conservative over time and school districts with larger proportions of white students than their states. In the third study, I evaluate the relationship between local CRT bans and exit among all teachers, teachers of color, and experienced teachers. In a small, matched sample of school districts with and without bans, I do not find differences in teacher exit by ban status for any of the three teacher groups. However, the number of districts included in these analyses was greatly reduced because of meaningful differences in contextual variables. Together, these findings suggest that while there are commonalities in language and values conveyed in these policies, the locations and potential consequences of CRT bans are highly dependent on context
Building Multiscale Models for Crack Propagation in Cold Spray Formed Polycrystalline Aluminum Microstructures
No full textResearch on robust predictive models for deformation and failure in modern materials, such as those produced by 3D printing, has been stymied by challenges in creating accurate representative virtual microstructures. This study presents a novel approach for faithfully modeling topologically complex, multi-scale microstructures by integrating SliceGAN, a generative adversarial network (GAN), with DREAM.3D, a synthetic microstructure generator. This coupling allows for the recreation of higher-order morphological properties and the generation of grains exhibiting key morphological and crystallographic distributions, in alignment with experimental data obtained from electron backscatter diffraction (EBSD) imaging. Although this work focuses on cold spray formed (CSF) microstructures, the newly developed integrated SliceGAN-DREAM.3D platform is versatile and applicable to a wide range of multi-modal microstructures, including those with micro-textured regions or parent grain formations. This work goes on to develop a robust, image-based, multi-scale micromechanical model to predict material behavior under deformation, including extreme phenomena such as fracture and fatigue failure. This is achieved through a self-consistent coupling of crystal plasticity finite element modeling (CPFEM) for coarse-grained crystals (CGs) with an upscaled constitutive model for a significantly higher population of ultra-fine grains (UFGs). Sub-volume elements are simulated to enable efficient computation, with the averaged response used to determine overall stress-strain and behavior and crack propagation
The Effects of Socio-Political Instability on Foreign Direct Investment Inflows: Empirical Evidence from the Kyrgyz Republic
Get PDFForeign direct investment (FDI) is an important driver of economic development, all governments want to attract it. However, socio-political instability often deters FDI inflows. This doctoral thesis systematically investigates and cross-sectorally validates, for the first time, the effects of socio-political instability on all types of FDI: total FDI, primary FDI, total non-primary FDI, manufacturing FDI, services FDI, financial intermediation FDI, and construction FDI.
Employing mixed research methods, the study combines quantitative regression analyses with qualitative case studies. The quantitative analysis utilizes time-series multiple regression models, applying an ordinary least squares (OLS) estimation method. These regression models are based on primary quarterly datasets from the National Bank of the Kyrgyz Republic, covering the period from 1995 to 2022 for total FDI and from 2007 to 2022 for sector-specific FDI. Qualitative observations from 1992 to 2022 provide depth and contextual insights, further supporting the findings. The regression results are validated through robust econometric estimation techniques.
The findings reveal that socio-political instability is associated with a significant reduction in FDI inflows, particularly affecting total FDI, manufacturing FDI, services FDI, and total non-primary FDI. Contrary to the existing body of knowledge, primary FDI is also highly sensitive to socio-political instability due to its inherent bilateral exclusive relationships with governments and associated environmental challenges and social implications. Conversely, FDI in financial intermediation and FDI in construction, areas not previously examined in the literature, demonstrate resilience to instability. Financial intermediation FDI are supported by inherent financial risk management, regulatory frameworks, and the mobility of financial assets. Multi-stakeholder participation in infrastructure projects mitigates and diversifies political risks, enhancing the resilience of construction FDI to instability. These findings fill a gap in the existing body of knowledge and have significant implications for policymakers and foreign investors. The study offers practical policy recommendations to minimize identified systemic risks and leverage opportunities related to resilience in the face of instability
REGRESSION IN SINGLE AND MULTILAYER NETWORKS WITH UNKNOWN LATENT MANIFOLD STRUCTURE
No full textIn recent times, various random graph models have gained popularity for their applicability in modeling real-life networks, for instance network of neurons in the brain of
an organism or protein-protein interaction networks. Latent position random graphs
comprise a particular category of random graphs, where each node is associated with a feature vector, also known as the latent position of the corresponding node. In real-world data the latent positions of an observed network are typically unknown and often inferential task involving the network concerns an inferential task on the latent positions. While the latent positions can have a large number of components, they
often exhibit an underlying manifold structure, that is, the latent positions often lie on a low dimensional manifold embedded in some higher dimensional ambient space. It is usually conjectured that while carrying out some inferential task on the set of datapoints with an underlying manifold structure, methods that exploit the presence of the underlying structure tend to produce better results than methods that
ignore the underlying structure. The goal of the work presented in this thesis is to
propose algorithms, with desirable asymptotic properties, for subsequent restricted inferential tasks on single or multiple latent position networks. Apart from establishing asymptotic convergence guarantees for the proposed algorithms, the presented research work further seeks to suggest small-sample improvements
HEAD INJURIES AMONG UNITED STATES AIR FORCE MAINTENANCE PERSONNEL
No full textBackground: Injuries threaten military personnel's health and unit operational readiness. While work activities performed by United States Air Force (USAF) personnel pose significant injury risks, this military branch has received little to no research attention. Maintenance personnel are critical to the Air Force's mission but face a myriad of injury risks, particularly those affecting the head.
Methods: The Air Force Safety Center provided us with all active-duty USAF maintenance personnel mishap data from January 1, 2012, through December 31, 2022. Both the first and second studies were cross-sectional. I calculated frequencies and ranked all injuries according to the body site affected. Using multivariable logistic regression, I explored the role of the maintainer's age, rank, gender, total hours of sleep, and duty hours as predictors of serious versus non-serious injuries. I reviewed 65 local USAF policies that addressed head injury prevention measures as well as Department of Air Force Manual 91-203. I focused on whether the policies incorporated the National Institute for Occupational Safety and Health's five Hierarchy of Control levels.
Results: Most maintenance personnel who sustained injuries were under 30 and were males. Of the eight general body regions, the head suffered the most injuries (40.6%), followed by the upper extremities (23.7%) and other head parts like the face, eye, and mouth (16.4%). Head injuries also ranked first among severe injuries (37.0%). I found significant associations between rank, gender, total hours of sleep, and the occurrence of severe head injury. My local policy review indicated that most bases rely heavily on personal protective equipment for workplace
hazards control. In contrast, the policy that applies to all USAF bases spans most levels of the Hierarchy of Control.
Conclusions: Work safety interventions should target the most severe injuries and the largest populations affected. I propose that policymakers and safety professionals prioritize the prevention of head injuries, which comprise the largest proportion of all injuries sustained, including those recognized as severe. Bases should consider adding additional head injury prevention measures that include not only personal protective equipment and administrative Hierarchy of Control levels but also elimination, substitution, and engineering controls
LIVING LONGER AND STRONGER: A MIXED METHODS STUDY OF DIMENSIONS OF AGING AMONG ADULTS LIVING WITH SICKLE CELL DISEASE
No full textBackground: Life expectancy for sickle cell disease (SCD) has more than doubled in the past 50
years. There is evidence that people with this condition may physically age faster than the general
population. Research is needed to quantify indicators of self-reported physical aging and qualitatively explore how affected individuals conceptualize older adulthood.
Objectives: This dissertation measures the prevalence and correlates of prefrailty/frailty and
physical function among adults with SCD in the United States during the early 21st century. We also seek to investigate how these adults define older adulthood’s onset.
Methods: In the first aim, we recruited 45 adults with SCD to a pilot study measuring prefrailty/frailty. In the second aim, with data from a multi-site registry, we compared the physical function of adults with SCD to the U.S. general population. To ascertain a modifiable biomarker’s potential contribution to physical function, we examined the association between hemoglobin and self-reported physical function. In the third aim, we interviewed adults with SCD to understand their older adulthood definitions and priorities for gerontology research.
Results: Aims 1 and 2 indicate that physical prefrailty/frailty measured by the FRAIL scale and
physical function limitation exist among adults with SCD. Hemoglobin was not associated with global
physical function. For the SCD phenotype sickle cell anemia (SCA), higher hemoglobin was cross-sectionally associated with higher odds of reporting no limitation in 3 challenging physical function subdomains. Adults with SCD defined older adulthood using 5 themes: (1) SCD’s cumulative impact, (2) Others’ lifespan with SCD, (3) Social determinants of health and lifestyle, (4) Statistical life expectancy, and (5) Social roles. Ideal future medical research should: (1) elucidate the timing of SCD sequelae and other comorbidities’ onset, (2) investigate SCD treatments and cure in middle/older adulthood, and (3) identify effective alternate pain management.
Conclusions: Prefrailty/frailty exists in SCD; this construct as measured by the FRAIL scale
partially aligns with frailty in the general older adult population. The potential relationship between hemoglobin and performing challenging physical function for SCA warrants further investigation. Varying definitions of older adulthood onset demonstrate that aging with SCD is not a uniform experience
Early-Life Gut Microbiome: Determinants and Cardiovascular Consequences
No full textThis dissertation investigated the role of early-life gut microbiome in childhood health, focusing on its maternal and environmental determinants, association with blood pressure (BP), and the potential mechanistic role of infant fecal metabolites. We used data from multiple prospective cohorts: (1) the Environmental Influences on Child Health Outcomes Cohort study, where mothers’ vaginal and/or fecal samples were collected during pregnancy and children’s fecal samples were obtained until age five; (2) the Copenhagen Prospective Studies on Asthma in Childhood 2010 cohort, where infant gut microbiome was measured at 1 week, 1 month, and 1 year, and child BP was measured at 3 and 6 years; (3) and the Canadian Healthy Infant Longitudinal Development cohort, where infant gut microbiome and metabolome were measured at 3 months and 1 year, and child BP was measured at 3 and 5 years.
Aim 1 quantified mother-child microbiota sharing up to five years. Both maternal pregnancy vaginal and fecal microbiomes contributed to the child’s gut microbiome, with the relative contribution of the vaginal microbiome increasing with when vaginal samples collected later in gestation. Mother-child microbiota sharing were influenced by prenatal antibiotic use, birth mode, and breastfeeding.
Aim 2 examined associations between infant gut microbiome and childhood BP. Higher α diversity and the presence of specific Bifidobacterium species in early infancy were associated with lower childhood systolic BP (SBP) in infants who were breastfed for at least six months. Early presence of Bifidobacterium was critical to the benefits of prolonged breastfeeding on childhood BP.
Aim 3 investigated how breastfeeding and Bifidobacterium longum subspecies infantis (B. infantis) affected infant gut microbiome composition and BP, and explored fecal metabolites as potential mechanistic links. Breastfeeding at three months was associated with lower childhood SBP, but only in infants colonized with B. infantis. Fecal metabolites, including acetic acid, creatinine, and succinic acid were linked to B. infantis, breastfeeding, and SBP.
Findings from this dissertation provide critical insights for interventions aimed at restoring beneficial microbes missing at birth, offer evidence for tailored strategies to optimize gut microbiome development in childhood, and identify microbiome targets for the primordial prevention of high BP