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Characterizing the Enantioselectivity of S-(2-succino) Lyase for Biocatalytic Carbon-Sulfur Bond Formation
Full text linkChiral sulfur-containing molecules are essential components of numerous pharmaceuticals, yet their synthesis traditionally relies on transition metal catalysts that can be energy intensive and pose environmental challenges. Biocatalysis offers a sustainable alternative, harnessing enzymes to carry out selective C–S bond formation under mild, aqueous conditions. This study investigates the enantioselectivity of S-(2-succino) lyase (2SL), a newly recognized carbon–sulfur bond-forming enzyme of the aspartase/fumarase superfamily
Roost Characteristics of Tricolored Bats in MCAS Cherry Point
No full textTricolored bats (Perimyotis subflavus) have experienced dramatic population declines, primarily due to the devastating effects of white-nose syndrome (WNS), a fungal disease that has caused mass mortality among bat species across North America. As this species faces an impending federal listing as endangered, there is an urgent need for proactive conservation measures to understand and manage its habitat needs. The lack of data on Tricolored bat habitat preferences in the NC Coastal Plains presents a significant gap in our understanding. My research aims to fill this gap by identifying the key factors that drive foraging and roosting site selection in this region. What we found is that Spanish moss was found at all four roost sites we tracked bats to, suggesting importance.
Role of Tolerance in Resistance Development in Escherichia coli Clinical Isolates
No full textAntibiotic treatment failure is responsible for over a million deaths per year worldwide. One of the causes of treatment failure is the development of antibiotic resistance, where bacteria are no longer susceptible to the antibiotic due to genetic changes or mutation. Resistance is identified by an increase in the minimum inhibitory concentration (MIC) for an antibiotic. Previous studies have shown that antibiotic tolerance precedes the development of resistance. Antibiotic tolerance is defined as survival of bacteria in the presence of a usually fatal dose of the antibiotic, without a change to the MIC. For our research, we aimed to study the association between tolerance and the development of resistance by first testing multiple Escherichia coli clinical isolates for differences in antibiotic tolerance. The differences in tolerance between the isolates were determined by a kill curve assay with clinically relevant antibiotics in the treatment of E. coli: levofloxacin and meropenem. The results of our study show that there are differences in tolerance levels between E. coli isolates using the antibiotic meropenem, however these differences are not as obvious using the antibiotic, levofloxacin. Future directions will involve testing the isolates showing the lowest and highest levels of tolerance for the development of resistance through in vitro methods. These results suggest that there are differences in tolerance to meropenem between clinical isolates of E. coli, and potentially differing levels of risk for the development of antibiotic resistance
COMPUTATIONAL (FPOCKETR) AND EXPERIMENTAL (FRAG-MAP) DETERMINATION OF RNA STRUCTURES THAT ENGAGE DRUG-LIKE SMALL-MOLECULE LIGANDS
Full text linkRNAs are critical regulators of gene expression, and complex secondary and tertiary structures often mediate their functions. Structured regions in RNA can selectively interact with small molecules – via well-defined ligand binding pockets – to modulate the regulatory repertoire of an RNA. However, the broad potential to modulate biological function intentionally via RNA-ligand interactions remains unrealized due to challenges in identifying compact RNA motifs with the ability to bind ligands with good physicochemical properties (often termed drug-like). Here, we devise fpocketR, a software package for identifying, characterizing, and visualizing ligand-binding sites in RNA. fpocketR was optimized, through a comprehensive analysis of currently available RNA-ligand complexes, to identify pockets in RNAs able to bind small molecules possessing favorable properties, generally termed drug-like. We experimentally confirmed the ligandability of novel pockets detected with fpocketR using a fragment-based approach introduced here, Frag-MaP, that detects ligand-binding sites in cells. Analysis of pockets detected by fpocketR and validated by Frag-MaP reveals dozens of newly identified sites able to bind drug-like ligands, supports a model for RNA secondary structural motifs able to bind quality ligands, and creates a broad framework for understanding the RNA ligand-ome. Lastly, we demonstrate fpocketR as a powerful discovery tool to analyze RNA-ligand interactions and novel pockets in small and large RNAs, to assess ensembles of experimentally determined and computationally predicted RNA structure models, and to identify pockets in dynamic RNA structural ensembles. Together, fpocketR and Frag-MaP create a powerful framework for understanding the potential of ligands to bind and manipulate cellular transcriptomes.Doctor of Philosoph
EXAMINING VALUE-BASED PAYMENT MODELS IN MEDICAID: IMPACT ON LOW-VALUE CARE UTILIZATION IN NORTH CAROLINA
Full text linkThe U.S. healthcare system continues to spend more per capita than any other nation without achieving commensurate health outcomes. A major contributor to this inefficiency is the persistent use of low-value care – services for which potential harms or costs outweigh likely benefits. Prior studies estimate that 6-8% of total U.S. healthcare spending may be attributable to low-value care. Beyond financial consequences, low-value healthcare services can directly harm patients and trigger cascades of unnecessary interventions. Despite growing awareness, low-value care use remains pervasive across the healthcare system.Value-based payment reforms aim to improve care quality while reducing unnecessary utilization and costs and thus represent a potential strategy for addressing low-value care. While the effects of value-based payment models on spending and selected quality metrics have been well studied, their impact on low-value care use among Medicaid population remains poorly understood. This dissertation addresses that gap by evaluating the effects of North Carolina’s Medicaid Transformation. In Aim 1, I estimate the effect of the transition to capitated managed care on low-value care utilization using an interrupted time series design. In Aim 2, I assess the impact of value-based payment elements of the Advanced Medical Home program, applying difference-in-differences estimation approaches. In Aim 3, I extend the Aim 2 analysis to examine potential spillover effects of the Advanced Medical Home program on low-value care utilization among Medicaid beneficiaries who remained in fee-for-service arrangements.Across three aims, the study found limited evidence that North Carolina’s value-based payment reforms significantly reduced low-value care use among Medicaid beneficiaries. While some low-value care services declined over time, most changes may not be definitively attributable to the reforms. The absence of strong incentives and low-value care specific benchmarks likely limited their effectiveness, with minimal evidence of both direct and spillover effects on provider behavior. A longer implementation timeline may be needed for practice-level investments and behavior change to translate into measurable reductions in low-value care utilization. These findings offer important insights for policymakers seeking to align incentives, eliminate waste, and improve value in Medicaid delivery systems.Doctor of Philosoph
From the Ground State to the Particle Emission Threshold: Nuclear Resonance Fluorescence in Zn-68
Full text linkDriven by recent advances in the understanding of coexisting shapes in the even-even Ni isotopes, the structure of neighboring Zn-68, the isotone of Ni-66, is investigated using nuclear resonance fluorescence. Low-spin levels were excited by linearly polarized photon beams at energies ranging from 3-10 MeV, covering the entire spin-1 excitation range of the nucleus below the particle emission threshold. In addition, γ − γ coincidence data enabled the study of the low-energy level scheme, populated from a high-energy and low-spin entrance point in a long-duration, dedicated measurement. The new data resulting from this work is interpreted in the shell-model picture, revealing the involvement of a large number of orbitals active across a wide range of excitation energies in Zn-68. Specifically, calculations using two different model spaces and several effective interactions often used to describe nuclei in this mass region are compared to the experimental level scheme as well as to the evolution of dipole strength with excitation energy. As this work includes the first experiment with the newly-established Clover Array at the High Intensity γ-Ray Source facility, the coincidence capabilities of the instrument are explored in detail. By utilizing numerous combinations of detector types and coincidence gating techniques, the nature of the decay and structure of Zn-68 are examined from various perspectives. The timing capabilities of scintillator detectors is leveraged, as well, demonstrating the ability to measure level lifetimes as short as 10-100 ps with the new array.Doctor of Philosoph
PREDICTING OVERUSE KNEE INJURIES IN MILITARY CADETS: FROM RISK IDENTIFICATION TO SCALABLE BIOMECHANICAL SCREENING
Full text linkOveruse knee injuries represent a critical challenge to military readiness, accounting for over 50% of medical visits and imposing substantial healthcare costs. This dissertation employed a systematic approach to identify high-risk subgroups, develop prediction models, and evaluate practical biomechanical assessment methods for overuse knee injury prevention among military cadets. The first study examined the relationship between pre-academy knee pain history and subsequent overuse knee injuries in 5,820 first-year cadets across three U.S. service academies. Results demonstrated that cadets with prior knee pain exhibited elevated injury risk (RR: 3.09; 95% CI: 2.63-3.65) and rate (IRR: 4.08; 95% CI: 3.31-5.02) compared to those without prior lower extremity injury. Incidence rates varied substantially by injury history, ranging from 149 per 1,000 person-years among uninjured cadets to 613 per 1,000 among those with prior knee pain. Notably, combining prior knee pain with other lower extremity injuries did not produce additive risk effects, suggesting anatomically specific injury history serves as a primary driver of future injury risk. Building upon this risk stratification, the second study developed and internally validated a multivariable prediction model among 1,265 first-year cadets with recent knee pain history. The model incorporated sport and physical training history, lower extremity isometric strength, and jump-landing biomechanical assessments. The model demonstrated moderate discrimination (AUC = 0.66; 95% CI: 0.65-0.67) and the decision curve analysis indicated the model would correctly identify 29 additional high-risk cadets per 100 evaluated compared to standard care, supporting its clinical utility for targeted prevention efforts. The third study addressed the practical implementation challenge for measuring biomechanical predictors in the field by evaluating OpenCap, a markerless motion capture system. Among 33 healthy participants, OpenCap demonstrated excellent intersystem reliability (ICC = 0.93-1.00) and test-retest reliability (ICC₂,ₖ = 0.92-0.98) across 90% of analyzed joint angles. The system successfully distinguished between natural and simulated risky landing patterns (AUC = 0.92; 95% CI: 0.90, 0.94), offering an accessible alternative to costly and cumbersome traditional marker-based systems.Collectively, these findings establish a framework for overuse knee injury prediction in military training populations. Prior knee pain history emerges as a practical initial screening criterion for identifying high-risk cadets, thus reducing the size needed to screen from inbound cadets, while validated prediction models can guide targeted interventions within this population. The demonstrated low system error and excellent reliability of markerless motion capture technology provides a field-ready solution for implementing biomechanical assessments at scale.Doctor of Philosoph
INNATE IMMUNITY MODULATES ANTIBIOTIC EFFICACY AGAINST PSEUDOMONAS AERUGINOSA IN MUCO-OBSTRUCTIVE AIRWAY DISEASES
Full text linkMuco-obstructive airway diseases (MADs) are characterized by the accumulation of dehydrated airway mucus. Individuals with MADs frequently suffer from chronic bacterial infection of the airway, in which Pseudomonas aeruginosa is typically the dominant end-stage pathogen. A hallmark of chronic infection is substantial neutrophil mediated inflammation. A primary contributor of P. aeruginosa driven morbidity and mortality is antibiotic treatment failure. The high frequency of treatment failure is not explained by antibiotic resistance, but rather caused by antibiotic tolerance, a phenotypic state that enables bacteria to survive antibiotic treatment without an accompanying shift in minimum inhibitory concentration. The mechanisms that drive antibiotic tolerance in the MADs infection environment are poorly understood. We investigated the contribution of mucus and neutrophils towards antibiotic tolerance. First, we showed that the accumulation of mucus promotes the formation of tobramycin tolerant aggregates. High concentrations of mucus impaired flagellar motility, which drove aggregate formation; flagellar mutants exhibited hyper-aggregative and hyper-tolerant phenotypes. We also showed that neutrophil elastase, a prominent neutrophil derived protease, impairs flagellar motility and drives antibiotic tolerance. Second, we investigated how the impact of calprotectin, the most abundant neutrophil derived protein in the MADs lung environment, impacted antibiotic treatment outcomes. Our data indicate that calprotectin mediated zinc-starvation results in increased susceptibility to tobramycin, but decreased susceptibility to meropenem and ciprofloxacin. We found that calprotectin exposure lowers translational fidelity and suggests a potential synergistic relationship with tobramycin. Finally, our data show that direct co-culture with neutrophils promotes tobramycin treatment failure and as primarily driven by NETs. Lastly, co-culture of P. aeruginosa with neutrophils results in increased citrullinated histone H3 while leaving neutrophil cells intact, suggesting that NET release in our system is mediated by vital NETosis rather than lytic NETosis. Overall, our data describe the significant impact of neutrophil activity on antibiotic treatment outcomes of P. aeruginosa in MADS and highlights the importance of developing accurate in vitro models for studying in vivo phenotypes such as response to antibiotic treatment. Understanding how various aspects of the MADs chronic infection environment contributes to antibiotic treatment failure is imperative for improving future treatment options.Doctor of Philosoph
Enhancing graph-based analysis of single-cell data to identify immunological correlates of disease conditions
Full text linkRecent advances in single-cell technology have facilitated the generation of rich datasets consistingof protein and gene expression measurements at a single-cell resolution. These data have deepenedscientific understanding in a variety of disease contexts and therapeutic areas, but they require a principledapproach to make sense of the generated data; graph-based methods are often a part of this principledapproach because of the information-rich structure of graphs. In this thesis, we contribute to the ongoingwork of graph-based method development for single-cell data analysis by first benchmarking existingdata processing workflows for their accuracy in downstream analysis tasks and second proposing newgraph-based methods for processing and analyzing these data. First, we analyze the combined effectsof downsampling methods and graph density on downstream graph-based analysis tasks. This allowsresearchers to understand more deeply how graph representations influence downstream analysis resultsand thus choose parameters and methods for graph representations of single-cell data in a principledway. In conjunction with this experimental analysis, we state and prove theoretical results regarding therelationships between clustering resolution, dataset size, graph density, and the number of communitiesidentified by the Leiden clustering algorithm. Second, we propose SpatPro, a graph-based featurizationpipeline that extracts biological insights from the spatial patterns in multiplexed spatial proteomics data.This work addresses needs in the field for both 1) interpretability of machine learning results and 2)accuracy in the face of limited availability of training data. Finally, we propose Cell-Aware SuperpixelRefinement (CASPR), a superpixel-based segmentation method for multiplexed spatial proteomicsdata. The CASPR method contributes to the field by maintaining strong adherence to groundtruth cellboundaries and efficiently encoding biological signal, as evidenced by the ability to generate highlyaccurate sample-level diagnostic predictions from the CASPR segmentations. This body of contributionsenhances the ability of the field to create reliable graph representations of single-cell data for downstream analysis, segment multiplexed spatial proteomics data with significant morphological heterogeneity, andgenerate biologically interpretable encodings of these multiplexed spatial proteomics data.Doctor of Philosoph
Il problema della macchina nell'opera di Primo Levi
Full text linkThe aim of my dissertation is to explore the role that the concept of the machine plays in Primo Levi’s writings. My critical reading follows the path traced by the various figures of the machine which punctuate Levi’s literary works; through the dialogue those figures weave together, the Turin-born author offers indeed a literary reflection that sheds new light on the implication between the duty to bear witness and the need to write, a crucial concern in his literature. The two periods of his work – the first, which coincided with novels about his experiences in a Nazi concentration camp and his return journey, If This Is a Man (1947) and The Truce (1963), and the second, which included the science fiction stories collected in Natural Stories (1966) and Defect of Form (1971), and the book on work as montage, The Monkey’s Wrench (1978) – enlighten each other actually from the notion of ‘machine’. In Levi’s literary work, the machine occupies the position of subject and of object of narration. The ‘operation dynamic’ of this dual significance of the machine is the threshold on which what I believe to be the challenge of Levi’s writing is played out: to offer a ‘testimony of the machine’ in the very core of the twentieth century, showing the power exercised by machines and the various ways in which the efficiency of techno-scientific rationality has altered humanity. In addition to being the literary scene in which the machine is the object of testimony (from a thematic point of view), Levi’s work is also the scenario in which the machine seems to take the place of the witness and become itself the subject of testimony. The machine is the uncanny element that remains ‘operational’ in the complex unity of Levi’s literature, revealing itself as its meta-narrative aesthetic and ethical driving force. My ‘anthology of machines’ presents itself as an ontology aiming at investigate the density of the machine as a key-concept from which emerges, within Primo Levi’s literary work, the network linking together not only testimony and writing, but also technique and art, nihilism and humanism.Doctor of Philosoph