18525 research outputs found
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Rising Waters, Uncertain Future: A History of Litigation in the Wake of Hurricane Harvey
No full textHistory Department Honors Thesi
How the Montessori Teaching Method Benefits Infants’ Fine Motor Skills
No full textFine motor skill development plays a crucial role in early childhood education, influencing academic performance and cognitive growth. This study examines the effects of the Montessori teaching method on infants’ fine motor skills, particularly pen gripping techniques and handwriting progression. A randomized controlled trial (RCT) was conducted with 40 children aged 3 to 5 years, divided into an experimental group receiving Montessori-based interventions and a control group following traditional instructional methods. Standardized assessments, including the Beery-Buktenica Developmental Test of Visual-Motor Integration (Beery VMI), a block-stacking task from the Bayley-III Motor Scale, and a geometric patterns task, were used to evaluate fine motor development. Results revealed a significant positive association between grip type and handwriting proficiency, with more advanced grip types linked to higher handwriting stages (β = 0.70, p = .017). Grip consistency also correlated with visual-motor integration, as children with more stable grip types demonstrated significantly higher Beery VMI scores (F(2,32) = 6.07, p = .006). The Montessori intervention significantly improved grip type development (F(1,25) = 11.43, p = .002) but did not produce significant effects on Beery VMI (F(1,27) = 1.17, p = .290) or geometric pattern scores (F(1,22) = 0.27, p = .610). These findings suggest that Montessori-based activities effectively enhance fine motor dexterity, particularly grip refinement, but may require additional components to foster broader visual-motor integration. Future research should explore long-term effects, expand sample sizes, and incorporate complementary interventions to optimize fine motor skill training in early childhood
Investigating the Effects of Genetically Regulated Gene Expression on Neurological, Cardiovascular, and Psychiatric Health
No full textIt is a matter of both clinical and scientific import to improve our understanding of how genetic variation influences the human brain in the contexts of both health and disease. Genetically regulated gene expression (GReX) often mediates the physiological consequences of germline variants as is evidenced by numerous transcriptome wide association studies (TWAS). To capture the consequences of GReX on human brain architecture, we conducted TWAS on over 3,500 heritable neuroimaging derived phenotypes (NIDPs) from the UK Biobank. The resulting transcriptional atlas of the human brain details associations between GReX of over 7,000 genes and NIDPs representing neurological structure, connectivity, and functional coactivation. GReX changes in both the brain and select somatic tissues demonstrated widespread, highly significant consequences for neuroanatomy. We identified 7 genes previously associated with structural heart measures that also predicted neurological changes, supporting transcription mediated, organ-level pleiotropy. The transcriptomic signature of Schizophrenia tagged a set of NIDPs that was statistically enriched for cortical regions affected in individuals with the disease. The same pattern was reduced in Parkinson’s and absent in Alzheimer’s, indicating that transcriptomic prediction of disease-relevant brain features is possible but sensitive to pathophysiology. Lastly, we leveraged whole blood TWAS reference panels trained in admixed populations enriched for African and indigenous American genetic ancestry to expand the set of brain-related GReX associations. Applying the admixed models to the UKB neuroimaging data, we expanded the set of GReX-NIDP associations in NeuroimaGene by 145%. Analysis of these data identified modules of genes that influenced network-like clusters of white matter tracts and adjoining cortical regions, many of which also demonstrated functional coactivation with each other. Together the work detailed here extends the molecular phenotyping of the brain using data from multiple ancestral backgrounds, highlights mechanistic avenues across the body through which genetic variation may impact brain health, and provides a sweeping array of candidate molecular mechanisms that may underlie empirical brain changes observed in the context of neurological and psychiatric disease
Computation-Driven Development of Next-Generation Viral Vaccines and Antibody Therapeutics
No full textDespite successful antiviral countermeasures dating back thousands of years, billions of human infections still occur annually, and pandemic viruses with high mortality rates continue to emerge, often with long wait times for effective interventions. Monoclonal antibody therapeutics and subunit vaccines represent promising technological advances that can offer two important advantages over traditional approaches: enhanced safety profiles and protection against a broader range of viral strains. This dissertation presents research advancing three aspects of next-generation antiviral countermeasures. In Chapter 2, I develop contrastive learning methodologies for antibody epitope representation, establishing both straightforward sequence-feature rules for identifying overlapping-epitope antibody pairs and two antibody language models with epitope-specific embeddings. The more generalizable model, trained across 250 antigen families, demonstrated 50% success in discovering HIV-1 antibodies with epitope overlap to the broadly neutralizing antibody 8ANC195. Chapter 3 details the characterization of one of the most broadly reactive coronavirus spike antibodies identified to date, contextualizing its binding properties and sequence features within the landscape of other cross-reactive coronavirus antibodies. Chapter 4 presents the development of linear epitope-focused influenza vaccines that result in heterosubtypic neutralization, reduced viral load in challenge models, and pan-influenza binding monoclonal antibodies targeting the fusion peptide. Collectively, this work advances our understanding of antibody-antigen interactions and provides novel computational and experimental frameworks that will contribute to the development of broadly protective viral vaccines and antibody therapeutics
The Role of Extracellular Matrix Alterations Induced by Radiation Therapy in Modulating Breast Cancer Recurrence
No full textTriple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with high metastatic potential, and radiation therapy (RT) is a crucial treatment strategy. However, despite its effectiveness in reducing recurrence overall, many patients with TNBC experience relapse, suggesting that irradiation may play a significant role in promoting a pro-tumor microenvironment. This dissertation investigates the impact of RT-induced extracellular matrix (ECM) remodeling on tumor recurrence, with a focus on structural, molecular, and mechanical properties of the ECM. We employed a combination of in vivo and ex vivo irradiated models, including non-tumor bearing and tumor-bearing models, to assess how RT affects ECM properties that regulate cancer and immune cell behavior. Our analysis of murine mammary fat pads revealed significant ECM alterations following RT, including increased collagen deposition, enhanced fiber density, increased tissue stiffness, and changes in the expression of key ECM components such as collagen I, IV, VI, and fibronectin. Utilizing decellularized ECM (dECM) hydrogels, we successfully replicated the in vivo irradiated microenvironment and studied its effects on tumor and immune cell proliferation, invasion, and function. Our results demonstrate that RT-induced ECM structure and composition modifications create a permissive platform for breast cancer cell growth, invasion, and immune modulation, especially in an immunocompromised context known to correlate with post-RT relapse. Notably, TNBC cells co-cultured with macrophages in irradiated dECM hydrogels led to macrophage polarization toward an immunosuppressive phenotype, which further enhanced tumor cell proliferation in both ex vivo irradiated and in vivo irradiated tumor-bearing models. Additionally, RT-induced ECM remodeling promoted cancer and immune cell metabolic reprogramming and facilitated ECM uptake. In conclusion, our study underscores the critical role of ECM remodeling in the RT response, highlighting its contribution to tumor growth and invasion as well as immune suppression in TNBC. These findings provide new insights into how targeting ECM-immune cell interactions may improve RT outcomes and reduce the likelihood of cancer recurrence
Modernizing Missouri’s Academic Program Management: Balancing Statewide Oversight and Responsiveness
No full textLeadership Policy and Organizations Department capstone projectThis mixed-methods study evaluates Missouri's academic program approval and review processes through stakeholder perspectives, neighboring state practices, and program performance data. Research identifies four challenges: process complexity causing implementation delays; barriers to data integration; limited institutional collaboration; and tensions between oversight and innovation. Through document analysis and 17 stakeholder interviews across Missouri's public institutions, plus comparative analysis of eight neighboring states, the study provides evidence-based recommendations to enhance academic program governance. Recommendations include creating collaboration frameworks, streamlining approval processes, enhancing data integration with comprehensive dashboards, and establishing continuous improvement mechanisms.Peabody College of Education and Human DevelopmentDepartment of Leadership Policy and Organization
Calculating Interfacial Thermal Transport Using Atomistic Simulation Methods
No full textAt the nanoscale, many materials have properties different than they do in the bulk. Nanomaterials can exhibit interesting and useful optical, electronic, and physical properties. However, the very features that give these materials their novel applications also impact their thermal transport properties. Poor transport can negatively impact device function by limiting the ability to deliver thermal energy where it is wanted and remove waste heat from where it is not. A fundamental understanding of the mechanics of thermal transport at the nanoscale is required to successfully mitigate these transport issues without altering the nanomaterial in a way that destroys its unique properties.
In this work, we use atomistic modeling methods to examine the fundamental mechanisms of thermal transport at the nanoscale. The work uses two modeling methods to examine two unique nanoscale transport problems. The first method is density functional theory, which was applied to thermal transport in an AlN/GaN superlattice structure. We solved the Boltzmann transport equation using properties from density functional theory to show that the primary driver of the low thermal conductivity in the AlN/GaN superlattice was an increase in scattering rather than a reduction in phonon group velocity due to zone folding.
The second method is molecular dynamics, which focused on methods to include the thermal transport contributions of electrons in metallic systems. Molecular dynamics simulations are classical, and do not natively support electronic effects. This shortcoming has hindered the use of molecular dynamics simulations to model thermal transport in materials with delocalized electrons. We present a two-temperature model to include the effects of electronic thermal transport and demonstrate its use on Nickel. We also apply it to a graphite-coated Nickel catalyst system to model thermal transport in the catalyst under inductive heating. Next steps for further development of the two-temperature model are also discussed
Essays on China's Urban Land Allocation and Spatial Economics
No full textThis dissertation examines the multifaceted impacts of local government land allocation decisions on urban welfare, resource distribution, and demographic trends in China. In the first chapter, we document a systematic and geographically dispersed price gap between industrial and residential land that contradicts the predictions of traditional efficient allocation models. By developing a quantitative spatial model in which local governments balance the allocation of fixed land quotas to attract both firms and workers, we show that weak labor mobility leads to an oversupply of industrial land—particularly in cities with higher productivity and amenities. An algorithm inspired by deep learning techniques is used to solve and calibrate the model, revealing that significant reductions in industrial land shares could enhance allocation efficiency.
The second chapter investigates the unintended demographic consequences of these land allocation policies. Employing a dynamic spatial overlapping-generation framework, we capture the interplay between governments' prioritization of industrial land, public education spending, and household family-planning decisions. The analysis demonstrates that the industrial discount in the land market indirectly raises housing prices, thereby reducing fertility rates and contributing to China’s population decline. Counterfactual simulations suggest that a shift toward a free land market could potentially narrow the fertility rate gap by over 16%, while also intensifying geographic disparities in fertility rates across cities.
Together, these studies contribute to a deeper understanding of the trade-offs inherent in urban land allocation decisions. The findings offer valuable policy insights for enhancing urban resource allocation, improving economic efficiency, and addressing demographic challenges in rapidly developing urban regions
Bodies Turned Objects: Transinstitutionalization, Disability, and Indigeneity in the Nineteenth Century
No full textThis dissertation is about how bodies traveled after death to, from, and between scientific and medical collections in nineteenth century United States and Western Europe. I investigate how museum curators, scholars, physicians, and other professionals trafficked, collected, and studied bodily materials labeled as “pathologies,” “curiosities,” “monstrosities,” and “abnormalities.” I also trace the collection and theft of the bodies and body parts of Native and Indigenous peoples, especially those who practiced culturally important bodily modifications or “deformations,” as well as the broader meanings and implications for families and communities. This dissertation reveals a tangled web of bodies that were sourced from all around the world traveling between collections throughout the United States and Europe. I examine how professional scientists and medical men created meanings for the bodies they were collecting and how those meanings were then used to justify, amongst other things, the collection of yet more bodies. Those meanings, assigned by scientists and physicians, placed those bodies within logics of race, disability, pathology, bodily normativity, and Indigeneity.
I show how vast collections of bodies were the working objects of the nineteenth century life sciences, which has given the bodies within those collections a long post-mortem ‘life’ that extends to the current day. I use three major lenses to analyze the bodies as they traveled through these collections: 1) transinstitutionalization, 2) de-identification and re-identification, and 3) proxification. By using these lenses to focus on the bodies as opposed to specific men of science or medicine (or the collections they governed), I provide a new analysis of what people’s bodies were doing, affording, and authorizing in the production of scientific knowledge
Compact Modeling of Epitaxial-Layer Properties and Radiation Effects in AlGaN High Electron Mobility Transistors
No full textHigh electron mobility transistors (HEMTs) have been of significant interest in power electronics. While gallium nitride (GaN) has been a suitable material for HEMTs, materials such as aluminum gallium nitride (AlGaN) have been emerging as potential candidates due to their higher breakdown voltage and radiation tolerance. However, very little HEMT compact modeling has been tailored to these new material systems or applicable in radiation environments. Utilizing transfer length method (TLM) structures, the channel resistance is studied as a function of epitaxial-layer properties and prompt photocurrent, and a compact model is created to model these effects. The concepts from this model are extended to a HEMT and allow for use in SPICE circuit design, such as modeling a boost converter circuit during a prompt photocurrent event. This model provides a new tool for working with HEMTs, providing tunable parameters to match the epitaxial-layers and prompt photocurrent behavior