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Control and Thermodynamics of Superconducting Qubits with Non-Hermitian Dynamics
No full textAs quantum systems are understood better from a fundamental physics perspective, we are gaining more insight and ideas for their many applications. Among them are quantum computation, sensing, and materials. Some difficulties that have been encountered are short lifetimes and coupling to unwanted modes while attempting to control these systems, resulting in error propagation. Previously, physicists have pursued Hermitian descriptions of systems to preserve unitary evolution and real-valued measurements. However, non-Hermitian systems not only provide a realistic description of physical systems within larger environments, but also a rich topological landscape from their complex energy spectrum. In this thesis, we will explore how to control a non-Hermitian qubit to utilize its complex spectrum and the role of its Hamiltonian in energetics and time dynamics. Because superconducting qubits offer flexibility in parameter tuning, we can tune the values of the non-Hermitian Hamiltonian to explore this complex spectrum across regions of both \PT-symmetry and \PT-symmetry breaking. This complex energy spectrum forms a Riemann surface that has a branch cut and branch points (exceptional points). Encircling these exceptional points adiabatically allows for state transport that can non-trivially convert between eigenstates. Previous experimental studies of this process revealed a chirality: eigenstate conversion occurs when following the state with higher gain, but breaks down when following the state with higher loss. We explore how the interplay between gain and loss in modes of the system results in the breakdown of this adiabaticity and how we can use a method based on shortcuts to adiabaticity to circumvent this. Finally, we leverage this tunability to further investigate how the components of the non-Hermitian Hamiltonian relate to classical thermodynamic notions of internal energy and work in time-dependent protocols via the Jarzynski equality
Biomarker and age at onset endophenotypes offer new insights into the genetic etiology of Alzheimer’s Disease
No full textIntroduction: Alzheimer’s Disease (AD) remains among the top 10 causes of death in the United States and is projected to affect nearly 14 million people by 2050. To this point, studies of Alzheimer’s genetics and endophenotypes have yielded a bounty of results that culminated in the first disease-modifying drugs, lecanemab and donanemab, in 2022. Most of the genetic studies for Alzheimer’s disease to date have been focused on late-onset AD or Autosomal dominant AD, leaving a critical need for studying sporadic early-onset AD (EOAD; ~10% of cases). Furthermore, the demand for clinical portability has created a need for high-sensitivity proteomic assays for plasma biomarker analysis. I aim to use some of the latest biomarker assays and age at onset (AAO) as endophenotypes in a genome-wide association study framework (GWAS) to uncover the genetics underlying AD and their biological implications. Broadly, I aim to answer the following question: how can genetic studies contribute further to our understanding of AD biology? Methods: In my first aim, I perform genetic analyses on concentrations of plasma amyloid-β peptides Aβ40 (n=1,467) and Aβ42 (n=1,484), Aβ42/40 (n=1,467), total tau (n=504), tau phosphorylated (p-tau181; n=1,079), and neurofilament light (NfL; n=2,058). GWAS and gene-based analysis were used to identify single variants and genes associated with plasma levels. Finally, polygenic risk score and summary statistics were used to investigate overlapping genetic architecture between plasma biomarkers, CSF biomarkers, and AD risk. In my second aim, I performed a multi-ancestry (non-Hispanic European, African, and East Asian) genome-wide association study (GWAS) including a total of 7,349 cases and 17,887 controls. Cases with an age of onset younger than 70 years were included. Sensitivity analysis, including cases with onset ≤65, was performed. Only controls older than 70 were included to decrease the risk of developing LOAD. Results: In my first aim, I found a total of six genome-wide significant signals. APOE was associated with plasma Aβ42, Aβ42/40, tau, p-tau181, and NfL. I proposed ten candidate functional genes based on 12 SNP-biomarker pairs and brain differential gene expression analysis. I found a significant genetic overlap between CSF and plasma biomarkers. I also demonstrate that it is possible to improve the specificity and sensitivity of these biomarkers when genetic variants regulating protein levels are included in the model. In my second aim, I identified eight novel significant loci: six in the ancestry-specific analyses and two in the trans-ancestry analysis. By integrating gene-based analysis, eQTL, pQTL, and functional annotations, I nominate eight novel genes that are involved in microglia activation, glutamate production, and signaling pathways. Discussion: I set out my aims with the goal of addressing my driving research question, “How can genetic studies contribute further to our understanding of AD biology?” Taking these results together and in the context of other researchers, this work has demonstrated that using age at onset and biomarker endophenotypes captures disease-relevant findings, such as elucidating the potentially key role of glutamate and synaptic homeostasis proteins in disease biology, especially affecting tau and neurodegeneration phenotypes
Understanding the role of E1OGDH1 in Root System Architecture and Nitrogen Response in Maize
No full textNitrogen fertilizers are an irreplaceable component of modern agriculture. However, due to the inefficiency of the crops bred, up to 70% of the applied nitrogen is not absorbed, and the resulting runoff creates environmental pollution. Roots play a crucial role in a plant\u27s well-being by absorbing nutrients and water and providing anchorage. The efficiency of these functions is significantly influenced by both the physiology and architecture of the roots. However, compared to above-ground parts, roots are understudied due to the inaccessibility of the organ and the complexity of the structure. This is particularly true for the genes underlying root system architecture, which remain largely unidentified due to the challenges associated with accurately capturing and measuring their complex morphological traits. In this dissertation, we identify E1OGDH1 as a mediator of Root System Architecture (RSA) and attempt to provide a hypothesis on the molecular mechanism using multi-omic studies. In Chapter 2, we delve into the process of identifying E1OGDH1 and characterize root crowns, focusing on the impact of natural and artificial alleles of the gene. Initially, we identify E1OGDH1 through Genome-Wide Association Studies (GWAS) of root crowns from a population specifically selected for high and low protein content in kernels, known as the Illinois Long Term Protein Selection Strains (ILTPS) population. We conducted two field experiments using recombinant inbred lines from the ILTPS population and phenotyped their root crowns using X-ray computed tomography. Additionally, we generated mutants in a B73 background and conducted a field experiment under nitrogen stress conditions. The CRISPR mutants employed a different root system architecture (RSA) strategy under nitrogen stress compared to the wild type. Our findings from the root crown phenotyping indicate that E1OGDH1 is mediating root architecture and nitrogen response. In Chapter 3, we utilize CRISPR mutants of E1OGDH1 grown under both high and low nitrogen conditions to conduct targeted metabolomics and transcriptomics studies. We collect leaf and root tissues from both wild-type and E1OGDH1 mutant plants and perform mass spectrometry to analyze TCA cycle organic acids, glycolytic metabolites, and free amino acids. Additionally, we conduct RNA sequencing (RNAseq) for transcriptomic analysis using these tissues. These comprehensive analyses provide valuable insights into the molecular mechanisms driving changes in RSA and responses to nitrogen stress. Overall, this work significantly advances our understanding of the role of E1OGDH1 in RSA and nitrogen stress response
Multiclass Liquid Biopsy Assessment of Neurofibromatosis Type 1 Associated Nerve Sheath Tumors
No full textNeurofibromatosis type 1 (NF1) is the most common inherited cancer predisposition syndrome and is characterized by the development of benign and malignant peripheral nerve sheath tumors. While plexiform neurofibromas (PNs) are frequent and often indolent, a subset progresses through atypical neurofibromas (ANs) to malignant peripheral nerve sheath tumors (MPNSTs), which are aggressive, therapy-resistant, and the leading cause of-cancer-associated mortality in NF1 patients. Early and reliable detection of malignant transformation and residual disease remains a clinical challenge due to limitations in current imaging, biopsy, and tumor heterogeneity in NF1 patients. In the first study, we used ultra-low-pass whole-genome sequencing (ULP-WGS) and cfDNA fragment size profiling to distinguish MPNSTs from PNs in 53 individuals. Tumor fraction and fragmentation features classified MPNSTs with 86% accuracy pretreatment and 89% during serial monitoring. Shorter cfDNA fragments and elevated tumor fractions were associated with MPNSTs, and dynamic changes in cfDNA tracked with tumor burden and treatment response. In the second study, we applied whole-genome cfDNA sequencing to a larger cohort of 101 NF1 patients and 21 controls. We analyzed fragmentomic features including bin-wise size ratios, end motifs, and nonnegative matrix factorization (NMF) to further resolve the tumor continuum. Fragmentomic signatures improved detection sensitivity for MPNSTs and enabled differentiation of ANs from both PNs and MPNSTs, achieving AUCs of 0.75–0.77 for these transitions. In at least one case, cfDNA analysis correctly identified malignancy where tissue biopsy misclassified the tumor. In the third and final study, we developed a targeted cfDNA sequencing assay in 82 individuals using a custom panel enriched for genes recurrently altered in MPNSTs. The integrated model, combining SNVs, CNAs, and structural variants (SVs), achieved a cross-validated AUC of 0.904 and outperformed tumor fraction estimates derived from genome-wide analysis alone. Serial sampling demonstrated the clinical utility of this approach for real-time monitoring: ctDNA detected a TP53 deletion prior to radiographic relapse in one patient, and complete ctDNA clearance was observed during remission in another. Together, these findings support a multimodal cfDNA-based strategy that integrates global fragmentomic and targeted mutational analyses for accurate, noninvasive detection and monitoring of malignant transformation in NF1. Given its scalability and precision, this approach may also inform liquid biopsy development in other solid tumors and heritable cancer syndromes
Echoes of the Dead: The Ancestral Motif in Pindar\u27s Victory Odes
No full textEpinician performance has generated lively debate, with little consensus. Due to lack of evidence, the ode’s première—its sights, sounds, and settings—remains largely unknown. Certain victory odes, though, do make one thing patently clear: not everyone was able to enjoy the performance in person. Specific members of the victor’s family—named fathers and uncles, for example—were missing, due to their preceding death. My dissertation focuses on these ancestral shades, who are both mysteriously absent and present in the odes. The four chapters of the project treat the variations on Pindar’s ancestral motif, used to negotiate the liminal presence of the dead. Sometimes, for example, the poet situates the victor’s ancestors quite close to the joyful moment of epinician celebration (Part One). On other occasions, by contrast, he relegates them to the distant darkness of Hades (Part Two). That separation elicits various kinds of poetic mediation, aimed at reaching the remote ancestors. With such outreach comes the temporal shift from epinician present to future, from première to subsequent reperformance. One kind of afterlife (ancestral) thus initiates another (literary), as Pindar looks to script his own lasting reception. In sum, this dissertation shows the different ways in which Pindaric epinician bridges the gap between the living and the dead; and it explores how such ancestral mediation informs both the poetry and (re)performance of the odes
Leadership and Management in Action Program (L-MAP) Supplement: Case Studies for Humanities and Social Sciences
Full text linkThe Leadership and Management in Action Program (L-MAP) Workbook and Facilitator Guide are authored by Erin Heckler, Ph.D., Jessica A. Hutchins, Ph.D., Molly Grisham, M.A., and Elizabeth Luckman, Ph.D., M.B.A. The L-MAP Project was supported by a Burroughs Wellcome Fund (BWF) Career Guidance for Trainees grant to Washington University in St. Louis, 2019-2021 (co-principal investigators: Erin Heckler, Ph.D., and Jessica Hutchins, Ph.D.).
This Supplement does not (nor does it intend to) replace the L-MAP curriculum. The case studies in this document are designed to accompany the theory in the L-MAP curriculum applying it to discipline-specific situations in the humanities and social sciences fields. Please refer to the L- MAP Workbook and Facilitator Guide for pre-work and to introduce theories and concepts at the beginning of each unit. Find the L-MAP Workbook and Facilitator Guide at https://sites.wustl.edu/lmap
Those gentle wolves : Reclaiming Little Red Riding Hood
Full text linkUndergraduate winner: 1st place, 2025, 38th Annual Carl Neureuther Student Book Collection Competitio
Biophysical insights into immunoglobulin interactions with influenza viral proteins
Full text linkInfluenza viruses cause a significant burden across the globe leading to thousands of mortalities annually. It remains challenging to acquire long-lasting immunity against influenza viruses due to the rapid rate of mutation within circulating strains and limited protection provided by seasonal flu vaccines. While the generation of influenza-specific antibodies provides a major source of protection against viral infection, our understanding of how biophysical properties of antibody-antigen interaction influence antibody protection against influenza viruses remains elusive. To address these challenges, we first developed imaging-based approaches in combination with computational models to elucidate the extent and mechanism of antibody inhibition of influenza virus assembly and release. We found that, depending on the binding orientation and target location of the antibodies, multivalent antibodies could adopt two “crosslinking” modes to achieve inhibition of viral shedding. Additionally, by establishing an in vitro system to mimic the competition between soluble antibodies and B cell receptors, we identified physical constraints that could limit effective B cell responses during repeated exposures to influenza viral antigens. Particularly, we found that membrane-proximal viral epitopes are at an inherent disadvantage for B cell recognition, due to steric hindrance by both directly and non-directly competing antibodies. Together, these insights call attention to the multi-faceted roles of antibodies in generation of long-lasting protection against influenza viral infection, highlighting the importance of optimizing epitope accessibility in current vaccine design strategies
Dynamic Spectral and Systems-Theoretic Approaches for Inference and Control of Heterogeneous Complex Networks
No full textNetworks of nonlinear systems are commonly employed to describe a diverse range of phenomena across physics, engineering, neuroscience, and biology. The undesirable behaviors of such systems, in the form of neurological disorders, power grid failures, or ecological collapses, have spurred significant interest in understanding their dynamic structures and developing effective control strategies. These systems are typically large-scale, consist of heterogeneous units, and are partially observable with limited measurement data, presenting theoretical and computational challenges for control design and connectivity inference. This thesis addresses these challenges by developing novel algorithms for pattern formation in populations of stable limit-cycle oscillators and connectivity reconstruction in complex networks from time-series data. The first part focuses on controlling nonlinear oscillator networks with heterogeneous units under aggregate population-level measurement constraints. The primary contribution is the development of a unified framework that leverages spectral approximation to transform the optimal control problem into a simple convex quadratic program with linear constraints, applicable to both open-loop and feedback control tasks within a model-based setting. We demonstrate its efficacy through numerical simulations and experimental validations on ensembles of electrochemical oscillators. The proposed framework is further extended to enable data-driven learning using aggregated measurements by characterizing the network synchronization patterns using the Fourier coefficients of the population mean. The second part of the thesis addresses the network reconstruction challenges arising from limited measurement data and partial node observations. We first present a data-efficient algorithm by formulating the network inference task as a bilinear optimization problem. An iterative algorithm with sequential initialization is proposed to solve the resulting bilinear program. We then tackle partial observability by integrating time-delay embedding with statistical learning techniques. The performance of the proposed algorithms is compared with existing methods across experimental and simulated datasets, comprising oscillatory, non-oscillatory, and chaotic dynamics. This thesis advances both control strategies for oscillator networks and inference techniques for nonlinear networks, contributing to the manipulation and understanding of complex dynamical networks
Chinese Students, Jim Crow Schools: Navigating Education in a Black-and-White Society
Full text linkPrevious research on the history of education in the Jim Crow South has largely focused on the effects of legal segregation on Black communities. However, there existed another group: the Chinese. In the seemingly bifurcated system, their intermediate status was particularly discernible in the school. After Lum v. Rice (1927) stipulated that Chinese people, as members of the “colored” race, should be excluded from white schools, Chinese families sought other forms of education, including private tutors and church-sponsored mission schools. Still, they remained steadfast in their commitment to accessing white public education. The Chinese reproduced, acquiesced to, and in some ways subtly challenged the racial hierarchy, encapsulating larger struggles relating to identity development, assimilation, power, and community relations. In this project, I use oral history interviews and archival material from Houston and the Mississippi Delta to analyze the school as a crucial site of racial formation. I argue that Chinese Americans in the mid-twentieth-century South came to understand their identities and race relations through interactions with the education system. While navigating deeply racist social contexts and educational institutions that rewarded assimilation, Chinese people learned to cope with oppression and negotiate their liminal position, striving to escape the unjust treatment of a group racialized as “colored” in the Jim Crow South. These stories underscore antecedents to the model minority stereotype, as well as the construction of Asian American identity in light of state-sanctioned white supremacy and anti-Blackness