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Impact Of Maternal Chronic Diseases In Pregnancy On Duration Of Infant Intake Of Breastmilk In The Postpartum Period, Danielle Nicole Lodge

Public Health Theses

Background: Chronic disease in pregnancy, including hypertensive disease, diabetes, and mental health disorders, is associated with adverse mother and infant health outcomes. Breastfeeding offers well-documented benefits, but currently, little evidence exists on how maternal chronic disease impacts the duration of breastfeeding postpartum, especially multiple chronic disease diagnoses. Objectives: To examine associations between maternal chronic disease and (1) duration of any breastmilk feeding through six months postpartum, (2) in-hospital infant feeding patterns, and (3) the impact of in-hospital breastmilk exposure on postpartum duration of breastmilk feeding among women with a chronic disease. Methods: This retrospective cohort study analyzed 1,294 maternal-infant records …

Implementing A National Electronic Health Record In The United States Using Insights From Similar Nations, Alexandra Webster

Public Health Theses

This thesis explores how the United States can implement a national electronic health record (EHR) system by drawing lessons from three comparison countries (Germany, Italy, and Austria) that have implemented their own national EHRs. A national EHR, distinct from local electronic medical records (EMRs), is a centralized or linked platform that consolidates standardized patient health data across all care settings. While a national EHR offers significant benefits, such as improved patient safety, better clinical decision-making and care coordination, more efficient allocation of care, and expanded capacity for public health research, it also presents challenges related to data security, data quality …

Glp-1 Receptor Agonist Use And Patient-Reported Well-Being Among Individuals With Diabetes And Obesity: Evidence From The All Of Us Research Program, Tinsae Gashachew Admassu

Public Health Theses

Abstract Background: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are widely prescribed for type 2 diabetes and obesity, with growing interest in their potential effects on mental health and functional outcomes. However, clinical trials often exclude individuals with psychiatric comorbidities, limiting generalizability. Objective: To examine the association between GLP-1 RA use and self-reported mental health and functional outcomes in individuals with diabetes and obesity using real-world data from the All of Us Research Program. Methods: This cross-sectional study analyzed 53,127 adults with type 2 diabetes and 35,430 adults with obesity who had both EHR and survey data. GLP-1 RA users were …

Period Poverty And The Politics Of Refusal: Building Menstrual Equity Beyond The State Through Mutual Aid, Alanah Armstead

Public Health Theses

This thesis examines period poverty as a consequence of systemic neglect, disproportionately affecting those made vulnerable by intersecting structures of racial, gendered, and economic injustice. Situating menstruation as a public health crisis shaped by policy failure, social stigma, and institutional disregard, this research critiques dominant legal and policy frameworks that approach menstrual equity through a limited scope that overlooks deeper structural inequalities rooted in race and class. This thesis explores how marginalized populations experience legal and welfare systems as sites of surveillance and moral judgment in the context of menstrual equity. Through seven semi-structured interviews with menstrual justice organizers, this …

Subsidized And Forgotten: The Quiet Erosion Of The Supplemental Security Income Program In American Social Policy, Johntrell Bowles

Public Health Theses

The Supplemental Security Income (SSI) program was created to guarantee a basic level of income security for the nation's most economically vulnerable populations: low-income elderly adults, people who are blind, and individuals with disabilities. Despite this foundational mission, SSI has stagnated over the past fifty years, becoming increasingly inadequate in addressing the economic and social realities of those it was designed to support.

This thesis examines how congressional neglect, enduring stigma toward welfare recipients, and outdated policy structures have eroded SSI’s ability to fulfill its original promise. Grounded in a critical social policy framework and informed by the author's professional …

Assessing Impact Of Maternal Proximity To Unconventional Oil And Gas Wells On Neonatal Birthweight In Ohio: A Retrospective Cohort Study (2010–2017), Alan Cao

Public Health Theses

AbstractBackground: Unconventional oil and gas development (UOGD) has expanded rapidly in the United States, particularly in states like Ohio, which is home to approximately 5,000 horizontal shale wells and more than 80,000 hydraulically fractured wells since 1952. Although oil and gas extraction has occurred in Ohio for over 60 years, the recent surge in UOGD activity has raised renewed public health concerns about environmental exposures during pregnancy. While previous studies have linked maternal proximity to UOGD with adverse birth outcomes, evidence remains limited regarding its association with birthweight and fetal growth indicators in high-production states such as Ohio.

Methods: We …

Statistical Methods For Investigating Cell-Type Specificity And Genetic Regulation Of Dna Methylation In Complex Traits, Youshu Cheng

Yale Graduate School of Arts and Sciences Dissertations

DNA methylation is one of the most widely studied epigenetic modifications that capture the cumulative effects of environmental exposures and inheritable effects and regulates gene expression. DNA methylation occurs at CpG sites, where the cytosine and guanine bases are connected by a phosphate group. Over the past decades, DNA methylation have been useful resources to understand the etiology and mechanisms of complex diseases. Multiple studies have linked DNA methylation with diseases to identify differentially methylated CpGs that associated with complex traits. In addition, another research direction is to focus on the single nucleotide polymorphisms (SNPs) associated with DNA methylation levels, …

Understanding Generative Models, From Theory To Applications, Zehao Dou

Yale Graduate School of Arts and Sciences Dissertations

Generative models - statistical and machine learning frameworks capable of producing new data samples - have emerged as powerful tools for modern artificial intelligence. This dissertation explores the theoretical underpinnings of generative modeling and examines their real-world impact across various domains. The work begins by delving into the mathematical foundations of probability distributions and latent variable methods, emphasizing concepts such as maximum likelihood estimation, variational inference, and adversarial training. Building on these core principles, it presents a unified perspective on popular architectures, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and score-based diffusion models. Empirical studies highlight how these models …

The Pulse And Press Of Change: Consequences Of Shifting Climate Regimes And Extreme Events In Big Sagebrush Plant Communities, Scott Carpenter

Yale Graduate School of Arts and Sciences Dissertations

Dryland ecosystems cover over 40% of Earth’s terrestrial surface and are critical to both biodiversity and human livelihoods, yet they are increasingly vulnerable to the interacting pressures of climate variability and land use. Effective management of these systems requires a deeper understanding of how chronic pressures and acute disturbances shape plant communities. This dissertation examines the interplay between climate variability, livestock grazing, and plant community dynamics in big sagebrush ecosystems of the Upper Green River Basin, Wyoming. Through three complementary studies, I demonstrate that while livestock grazing influences plant structure, its effects are consistently subordinate to climatic and edaphic factors, …

Tau-Connectome Predictive Modeling And Subtyping In Preclinical Alzheimer's Disease, Hamid Abuwarda

Yale Graduate School of Arts and Sciences Dissertations

Alzheimer's disease (AD) is characterized by the accumulation of amyloid-? and tau, yet clinical progression varies widely across individuals. The central aim of this dissertation was to evaluate whether functional brain connectivity derived from resting-state fMRI can serve as a clinically meaningful predictive tool in the asymptomatic phase of the disease, preclinical AD. In Chapter 2, I develop connectome-based predictive models linking whole-brain functional connectivity to regional tau positron emission tomography (PET) signal in the Anti-Amyloid Treatment in Asymptomatic Alzheimer's Disease (A4) Study. These models predicted tau burden, particularly in regions vulnerable to tau deposition in Braak stages IV/V. In …

Genetic Variants Linked To Neurodevelopmental Disorders Within The Beta3-Beta4 Loop Of The Trio Ph 2 Domain Release Autoinhibition Of The Trio Gef2 Activity, Melissa Carrizales

Yale Graduate School of Arts and Sciences Dissertations

The TRIO family of proteins, which includes Trio, Kalirin, UNC-73 (in Caenorhabditis elegans), and dTrio (in Drosophila), are key regulators of cell morphogenesis, migration, tissue organization, and neuronal development through their regulation of Rho GTPases. These proteins feature multiple catalytic and scaffolding domains that mediate GTPase activation and cellular localization. TRIO proteins are essential for processes like actin dynamics, cell migration, and synaptic function, and disruptions in their activity have been linked to neurodevelopmental and neuropsychiatric disorders. This study focuses on Trio, specifically its regulatory mechanisms and how disease-related mutations disrupt its catalytic activity, contributing to various human diseases.

In …

Individual-Level Large-Scale Circuit Modelling Of Human Cortex, Rachel Ann Cooper

Yale Graduate School of Arts and Sciences Dissertations

Individuality is a defining feature of human existence. Yet the neural mechanisms underlying such individual variation are not fully understood. Prior research has suggested that variation in the balance between excitation and inhibition within the brain may contribute to these differences. To investigate this hypothesis, we employed a large-scale, biophysically-based model of the human cortex. This model is governed by a small set of biologically interpretable parameters, allowing for a focused analysis of how shifts in excitation and inhibition shape individual brain function. Using this modelling framework, this thesis examined patterns of variation across both healthy individuals and clinical populations. …

Disability, Cure, And (Anti)Normativity In Modern And Contemporary Spanish Literature, Martha Engvall

Yale Graduate School of Arts and Sciences Dissertations

In my dissertation, I examine the role of disability, diagnosis, and cure in modern and contemporary Spanish novels. In the first three chapters, I show how authors of the late 19th and early 20th century used disability’s relationship to race, gender, and social class to question exclusionary social norms. I analyze critiques of industrialization in Galdós’s Marianela (1878) and Blasco Ibáñez’s Del vivir (1904); examine portrayals of leprosy in Galdós’s Misericordia (1897), Pardo Bazán’s La prueba (1890), Miró’s Del vivir (1904) and El obispo leproso (1926), and Hoyos y Vinent’s El monstruo (1915); and explore connections between disability, sexuality, and …

Three Essays On Homophily, Heterophily, And Network Inequality In Organizations And Markets, Yiftach Yarmar

Yale Graduate School of Arts and Sciences Dissertations

Homophily, the tendency to form relationships with similar others, is a defining feature of social networks that shapes access to resources and market outcomes. While homophily fosters trust and coordination, it also risks reinforcing existing inequalities by concentrating opportunities within dominant groups. This dissertation examines the dual role of homophily and heterophily in professional transactions, focusing on how these dynamics affect underrepresented groups in client-facing industries.

Through three empirical studies, the dissertation investigates homophily in organizational restructuring, client-agent selection in service industries, and real estate transactions. Across these settings, homophily does not yield uniform advantages or disadvantages. Rather, its effects …

Interpretable And Data-Driven Machine Learning Models For Analyzing High-Dimensional Biological Data, Junchen Yang

Yale Graduate School of Arts and Sciences Dissertations

High-dimensional biological data, including single-cell omics, are prevalent in modern biology for characterizing a wide range of biological processes and phenomena. Although our capacity to generate such data has expanded at an unprecedented pace, significant challenges remain in extracting the informative features and the underlying biological signals. In particular, these datasets not only exhibit high dimensionality but also suffer from issues including inherent noise, low signal-to-noise ratio, and intrinsic heterogeneity. While machine learning models hold great promise for analyzing such data, their complexity and sensitivity to data characteristics often impede biological interpretability. To address these interconnected challenges, this thesis develops …

Understanding And Quantifying Behavior For Unraveling Brain Function, Daiyao Yi

Yale Graduate School of Arts and Sciences Dissertations

Understanding the relationship between neural activity and behavior is fundamental to uncovering brain function. With recent advancements in hardware and computation, we can now collect and analyze high-resolution behavioral and neural data in complex, naturalistic settings. However, challenges remain in effectively modeling and disentangling high-dimensional behaviors, particularly in social and multi-subject contexts, where subtle variations may reflect individual differences or underlying neural states.

This thesis presents a series of structured, interpretable deep learning frameworks that address this challenge by modeling behavior and its neural correlates across multiple levels. First, I introduce the Constrained Subspace Variational Autoencoder (CS-VAE), which uses semi-supervised …

Aberrant Splicing Exonizes C9orf72 Repeat Expansion In Als/Ftd, Suzhou Yang

Yale Graduate School of Arts and Sciences Dissertations

A nucleotide repeat expansion (NRE) (GGGGCC)n in the first annotated intron of the C9ORF72 (C9) gene is a common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). While previous studies have shown that C9 NRE produces several toxic dipeptide repeat (DPR) proteins, how an intronic RNA segment can access the cytoplasmic translation machinery remains unclear.

By capturing and sequencing NRE-containing RNAs from patient-derived fibroblasts and neurons, I found that C9 NRE became part of an alternatively spliced exon 1 through the usage of various downstream 5ʹ splice sites. These NRE-containing splice isoforms accumulate in C9 ALS/FTD brains, …

Neural Representations For Digital Humans, Chengan He

Yale Graduate School of Arts and Sciences Dissertations

Humans, with complex structures and diverse attributes, pose significant challenges for digital modeling. One fundamental difficulty arises from the heterogeneous nature of humans, necessitating expressive yet efficient representations to faithfully capture fine details across different components. Moreover, even minor imperfections in digital humans can be highly perceptible, often leading to issues such as the uncanny valley. With the growing interest in the metaverse and digital human avatars, developing robust and high-fidelity representations for digital humans has become a pressing problem in computer vision and graphics, with significant implications for down-stream applications such as telepresence, virtual agents, and visual effects. In …

Movement Public Health: Addressing The Links Between Public Health And Carceral Systems, Marie Fatima Hyacinthe

Yale Graduate School of Arts and Sciences Dissertations

This dissertation is an interdisciplinary exploration of the links between public health and carceral systems, the connections between academic scholarship and advocacy, and the role of public health research in social justice movements. This dissertation begins with in-depth interviews with academic researchers and anti-carceral organizers, as well as analyses of my own experiences taking part in protests and mutual aid work, which ground conversations on the meaning of safety and care, and the role of public health. The second chapter is a systematic literature review and synthesis where I analyze academic literature about public health and carceral systems, assessing it …

Dynamical Mechanisms Of Neural Computation, Frederick Michael Berl

Yale Graduate School of Arts and Sciences Dissertations

The brain is one of the most complex dynamical systems in the universe and despite our everyday familiarity with it, the intricacies of how it functions remain a mystery to us. It is enormously powerful, continuously learning, and able to perform computations flexibly and adapt to novel situations. Although science presently has an understanding of how individual neurons work and a general idea of what the functions of each region in the brain are, how the computations of each neuron are modulated by context and how the various regions work together to produce behavior are unclear. Here, we explore the …

A Possible Mechanism Of Miwi2-Mediated Dna Methylation By De Novo Dna Methyltransferases, Tianshu Liu

Yale Graduate School of Arts and Sciences Dissertations

Epigenetic information refers to inheritable information that is not directly encoded in the genomic locus. Among various epigenetic mechanisms, DNA methylation play a crucial role in development and homeostasis and undergoes dynamic remodeling during mouse embryogenesis. In the mouse germline, primordial germ cells experience a global erasure of DNA methylation, a process important for the re-establishment of parent-specific methyl-imprint in the late stage of gametogenesis. However, how DNA methylation occurs at specific genomic loci remains an open question. Miwi2, one of three murine PIWI proteins, has been implicated in guiding de novo DNA methylation, yet the molecular machinery of Miwi2-mediated …

The Gnda Microprotein Supports Atp Homeostasis In Escherichia Coli During Heat Shock, Jessica Jayne Mohsen

Yale Graduate School of Arts and Sciences Dissertations

Same-strand overlapping, or nested, open reading frames (ORFs) can optimize the information content of size-constrained viral genomes by increasing the number of proteins expressed from a limited nucleotide sequence. However, nested small open reading frames (sORFs) were previously omitted from prokaryotic and eukaryotic genome annotations. It was therefore surprising when numerous nested sORFs were recently discovered in bacteria and eukaryotes. Our case study of the GndA microprotein in Escherichia coli provides evidence of an emerging model that overlapping genes can be expressed from bacterial genomes to contribute to cellular fitness. GndA interacts with the electron transport chain and ATP synthase …

Volatile Transport At Convergent Margins: Implications For Global Geochemical Cycles, Anne Alicia Haws

Yale Graduate School of Arts and Sciences Dissertations

The production and transport of metamorphic fluids are key to a range of Earth processes, including seismogenesis, global geochemical cycling, and the maintenance of planetary habitability over geologic time. It is therefore of great importance to understand the distribution of fluids in the lithosphere and how their interactions with rocks along deep flow pathways affect the transport of volatiles and dissolved species in metamorphic systems. This dissertation aims to trace metamorphic fluid sources and pathways in various petro tectonic settings, and to assess how fluid-rock interactions modify fluid compositions, with the goal of better understanding the processes underlying the global …

Adaptation Of Learning Dynamics And Feature Representations Via The Neural Kernel, Lianghui Peng

Yale Graduate School of Arts and Sciences Dissertations

The ability to learn from experience is essential for both biological and artificial agents. To learn efficiently in complex, high-dimensional environments, agents must generalize strategically from limited data by focusing on features relevant for the task. The generalization strategy, known as inductive bias, shapes the dynamics of learning. Previous works have established the theory of neural tangent kernels that describes the learning dynamics of artificial neural networks. However, a comparable framework for understanding and quantifying inductive bias in biological systems performing behavioral tasks remains underdeveloped. Here, we introduce a neural kernel framework to characterize inductive biases of humans and artificial …

Exploring Squamate Evolution Through Focused Taxonomic And Anatomic Lenses: A Taxon-Character Approach To A Taxon-Character Problem, Dalton Meyer

Yale Graduate School of Arts and Sciences Dissertations

Among the living terrestrial vertebrates, the greatest diversity of verifiable species is seenamong the squamates, the group which contains the lizards and snakes. With a global distribution limited only by their general intolerance to long periods of cold temperatures, they are a ubiquitous component of modern ecosystems. Furthermore, over their roughly 180-million-year evolutionary history they have achieved tremendous morphological disparity and a range of body sizes that spans three orders of magnitude. However, our understanding of the origins and early evolution of squamates remains obscured due to persistent conflict in hypotheses generated from morphological and molecular data. This discordance is …

A Second Wave Of Notch Signaling Diversifies The Intestinal Secretory Lineage, Eleanor Zagoren

Yale Graduate School of Arts and Sciences Dissertations

The small intestine is well known for its nutrient-absorbing enterocytes; yet equally crucial for homeostasis is a diverse set of secretory cells, all presumed to originate from the same intestinal stem cell. Despite their major roles in intestinal function and health, understanding how the full spectrum of secretory cell types arises remains a longstanding challenge, largely due to their comparative rarity. Here, I investigate the specification of a rare population of small intestinal epithelial cells found in rats and humans but not mice: CFTR high expressers (CHEs). Using pseudotime trajectory analysis of single-cell RNA-sequencing data from rat jejunum, I provide …

Valuing Cheap: Constructing, Consuming, And Contesting The Dollar Store Economy, Frances Evelyn Barrett

Yale Graduate School of Arts and Sciences Dissertations

In Valuing Cheap, Barrett traces the histories of Dollar General, Family Dollar, and Dollar Tree from the firms’ twentieth century origins in three distinct southern locales into corporate behemoths with more stores than McDonald’s or Walmart. Valuing Cheap provides an important chapter of the late twentieth century history of racial capitalism, detailing how dollar stores at once “served” local communities while capitalizing on existing spatialized, racialized, classed, and gendered inequalities. This history illuminates the interwovenness of business, consumer, and labor histories, emphasizing the fundamental entanglements of power, material and cultural production, and consumption. The dollar store industry’s cheap goods, low-wage …

Random Matrices And Statistical Inference With Correlated Structures, Haoyu Wang

Yale Graduate School of Arts and Sciences Dissertations

Random matrices play a central role in modern probability theory and high-dimensionalstatistics, both as fundamental mathematical objects and as powerful tools for inference. This dissertation presents several works on random matrix theory and its connections to statistical inference with correlated structures in high dimensions. On the random matrix side, we investigate the spectral properties of sample covariancematrices. Our approach is built upon the resolvent method, and we utilize local laws for various spectral analyses. Specifically, our contributions are three-fold: (1) we attain the first explicit rate of convergence for the largest eigenvalue of sample covariance matrices; (2) we derive the …

Russian Forms: Race, Sex, And The Making Of Russian Literature, Fiona Bell

Yale Graduate School of Arts and Sciences Dissertations

This dissertation argues that the elaboration of Russian racial imaginaries was coterminous with the construction of the Russian literary canon and Russian literary theory. Beginning with the global debates concerning the abolition of slavery and serfdom in the 1850s and concluding with the first wave of emigration from the Soviet Union in the 1920s, the dissertation demonstrates how canonical Russian authors—Ivan Turgenev, Fyodor Dostoevsky, Viktor Shklovsky, and others—wrote fiction that, in mobilizing the racial implications of intimacy, kinship, and heredity, articulated arguments about racial difference and the conceptual “fit” of “race” for the Russian Empire. Literary authors make arguments about …

Bridging Behavior And Neural Activity: Neural Dynamics Leading To Self-Initiated And Task-Driven Movements, Yongxu Zhang

Yale Graduate School of Arts and Sciences Dissertations

Understanding how populations of neurons generate behavior remains a fundamental question in neuroscience. While single-neuron analyses have provided valuable insights, behavior emerges from the coordinated dynamics of large neural ensembles that evolve over time and across states. A major difficulty is that neural population activity is non-stationary: it exhibits temporal distributional shifts, transitions between distinct dynamical regimes, and modulation by external or inter-regional inputs. Advances in artificial intelligence offer new opportunities to address this challenge. Yet, conventional models, such as standard recurrent neural networks, often fail to capture such complexity, limiting both predictive performance and mechanistic interpretability. This motivates the …