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White Matter-Associated Functional Connectivity in the Human Brain
No full textFunctional magnetic resonance imaging (fMRI) has traditionally focused on gray matter (GM), while blood-oxygen-level-dependent (BOLD) signals in white matter (WM) were often dismissed as physiologically irrelevant. However, growing evidence indicates that WM exhibits coherent and meaningful neural activity. This dissertation systematically explores the spatiotemporal organization, modulation, and clinical relevance of WM-associated functional connectivity (FC) and proposes a novel framework to characterize the WM-GM connectome. We begin by examining the anisotropic structure of spontaneous BOLD correlations in WM, characterized through the construction of functional correlation tensors (FCTs). Leveraging a large normal aging cohort, we identify region-specific aging effects on FCT-derived indices, providing detailed maps of age-related alterations in local FCT metrics. We further examine seasonal modulations of WM-GM FC in a healthy population. By modeling sinusoidal trends across seasons, we detect significant periodic variations in low-frequency fluctuations, global and network-level FC strength, and topological properties of brain networks. These variations correlate with environmental factors like daylength and temperature, highlighting the dynamic influence of external cycles on intrinsic brain organization. Extending to clinical context, we analyze WM-GM FC and network properties in individuals with preclinical Alzheimer’s disease (AD) or AD dementia, compared to controls. Our findings reveal that the WM-GM functional connectome undergoes regional and systemic dysfunctions as early as in the preclinical stage, correlating with amyloid deposition and cognitive impairment. Finally, we introduce a hypergraph-based model to capture high-order WM-GM interactions, revealing group-level differences in clustering coefficients and centralities that may serve as novel AD biomarkers. Overall, this work establishes WM functional connectivity as a systematic and clinically informative feature, expanding our understanding of the functional role of WM in the human brain
Atomic Accountability: Policy Framing and Public Opinion Concerning Sole Authority
No full textThe president is the only person who can authorize launch of a nuclear weapon. This policy, known as sole authority, emphasizes speed and decisiveness over deliberation. Many Americans have expressed discomfort over the policy and legislation has been proposed to curtail unilateral action by the president in this realm. With this in mind, the dissertation applies a mixed-methods approach integrating qualitative and quantitative data to investigate media framing and public opinion on sole authority. A novel theory regarding support for the current policy is also developed and tested. The dissertation comprises three interconnected projects. The content analysis chapter characterizes the information environment surrounding sole authority by identifying prevalent frames used by the media to report on the policy. While news coverage of the policy is variant, frame prevalence is relatively consistent across administration, policy stance, and partisan leaning of news sources. Frames emphasizing aspects of the decision-making process, a lack of trust in the president, and a lack of checks and balances are frequently employed by news media. Additionally, sole authority presents as a partisan issue in the news. The next chapter provides insights from twelve interviews with a non-random sample of American citizens. The interviews revealed that values tied to democratic norms tend to influence sole authority opinions and identified the main source of discomfort as the concern over a single decision-maker bearing responsibility for a decision of nuclear proportions. Public support for sole authority coincided with high trust in government procedures and/or the nuclear launch process. Nonpartisan opinions were also expressed in the majority of interviews suggesting that active open-minded thinking may attenuate the influence of partisanship on public opinion. Insights from the interviews were used to construct a theory concerning public support for sole authority. The survey experiment chapter tested this original theory as well as the viability of an alternative policy that incorporates a group decision-making process. This dissertation attends to a critical yet understudied issue area requiring prompt attention of both scholars and policymakers. Findings hold implications for potential policy changes, government responsiveness to public discomfort, and increased accountability for nuclear first-use situations
Targeting TREM2 in Postmenopausal Breast Cancer in Obese and Weight Loss Settings
No full textObesity is an established risk factor for breast cancer development and worsened prognosis; however, the mechanisms for this association - and the potential benefits of weight loss - have not been fully explored. The adipose environment surrounding breast tumors, which is inflamed in obesity, has been implicated in tumor progression. An emerging therapeutic target for cancer is TREM2, a transmembrane receptor of the immunoglobulin superfamily that is expressed on macrophages in adipose tissue and tumors. I utilized genetic loss of function (Trem2+/+ and Trem2-/-) models and dietary (lean, obese, and weight loss) intervention approaches to examine impacts on postmenopausal breast cancer. Remarkably, Trem2 deficiency constrained tumor growth in lean, but not obese or weight loss mice. Single-cell RNA sequencing, in conjunction with VDJ sequencing of tumor and tumor-adjacent mammary adipose tissue (mATTum-adj) immune cells, revealed that tumors of lean Trem2-/- mice exhibited a shift in clonal CD8+ T cells from an exhausted to an effector memory state, accompanied with increased clonality of CD4+ Th1 cells, that was not observed in any other diet-genotype group. Notably, identical T cell clonotypes were identified in the tumor and mATTum-adj of the same mouse. Finally, an immune checkpoint study demonstrated that aPD-1 therapy restricted tumor growth in lean and weight loss, but not obese mice. I conclude that weight history is relevant when considering potential efficacy of TREM2 inhibition in postmenopausal breast cancer. This work reveals immunological interactions between tumors and surrounding adipose tissue, highlighting significant differences under obese and weight loss conditions. In addition to pre-clinical studies, I also performed a retrospective study in breast cancer patient samples in which I analyzed the associations between TREM2+CD68+ cell density in three distinct regions of the tumor with multiple tumor characteristics, prognostic factors, and metabolic syndrome criteria. However, the data mostly demonstrated no associations between TREM2-expressing macrophages and tumor prognostic factors or metabolic syndrome criteria in early-stage ER+ breast cancer
Identification of Asporin as a HER3 ligand exposes a therapeutic vulnerability in prostate cancer
No full textCancer-associated fibroblasts (CAF) are part of the tumor microenvironment (TME) that enable cancer cells to establish metastases, but the mechanisms of these interactions are not fully known. Herein, we identify a distinct subtype of CAF that express a four-gene signature (CHTRC1, ASPN, FAP and ENG), termed CAFÉ CAF, that are enriched in the TME of aggressive prostate cancer and associated with worse patient outcomes. Furthermore, we identify a novel paracrine mechanism in which one of the CAFÉ CAF markers, ASPN, is secreted by CAF and activates ErbB signaling and subsequent migration of adjacent prostate cancer cells. Our data supports that ASPN binds directly to the ligand binding domain of HER3 to induce HER2/HER3 heterodimerization and activation of downstream signaling pathways including Phosphoinositide 3-kinase (PI3K), Mitogen-activated protein kinase (MAPK), and calcium signaling. Genetic and therapeutic inhibition of HER2 and/or HER3 ablate ASPN-induced signaling and migration. Clinically, ASPN is detected in the stroma of HER2/HER3-expressing human metastatic prostate cancer, supporting the clinical relevance of these findings and highlighting a potential therapeutic vulnerability. Antibody-drug conjugate (ADC) therapies designed to target either HER2 (trastuzumab deruxtecan) or HER3 (patritumab deruxtecan) significantly diminish prostate cancer cell growth in vitro as well as restrict tumor size in vivo, despite ASPN in the TME. Collectively, these findings indicate ASPN functions as a novel HER3 ligand to induce cellular migration, and inhibition of this pathway with either anti-HER2 or anti-HER3 ADC therapies highlights potential clinical utility for patients with metastatic castration-resistant prostate cancer (mCRPC) that expresses HER2 or HER3
Webcam-Based Cognitive State Detection for Software Developers: System Development and Cross-Domain Analysis
No full textCognitive monitoring systems increasingly assume that mental states manifest consistently across task domains, enabling universal deployment without domain-specific calibration. This research challenges this assumption through systematic cross-domain validation of webcam-based cognitive state detection across programming, mathematical problem-solving, and fatigue assessment contexts. Using a comprehensive processing pipeline built on MediaPipe Face Mesh, we extracted eye movement metrics including blink patterns, pupil dynamics, PERCLOS, and gaze characteristics from three established datasets: UTA-RLDD for fatigue detection, EMIP for programming-specific cognitive load, and Krejtz for mathematical cognitive load. Our findings reveal a fundamental dichotomy between universal fatigue detection and domain-specific cognitive load detection. Fatigue detection achieved strong cross-individual generalization with 84% accuracy using Leave-One-Subject-Out validation, demonstrating consistent physiological signatures dominated by blink-related features across different task contexts. In contrast, cognitive load detection exhibited substantial domain-specificity, with models achieving 67-76% accuracy within training domains but dropping to 22-31% accuracy when applied across domains—below chance performance, indicating systematic misclassification rather than random failure. The system achieved real-time performance suitable for practical deployment, with 12.3ms processing latency and modest computational requirements enabling integration with existing development environments. These results demonstrate that while fatigue monitoring can be universally deployed across cognitive contexts through consistent autonomic nervous system indicators, cognitive load detection requires domain-specific approaches that account for the distinct neural architectures and expertise patterns underlying different types of cognitive work. This domain-specificity challenges prevailing assumptions in cognitive monitoring re-
search and establishes empirical foundations for developing more effective, context-aware cognitive support
systems
Vital Infrastructures: The Affects, Power, and Environments of Infrastructural Media
No full textThrough drawing attention to the media archives created in, around, and about infrastructures, I argue that infrastructures are media apparatuses of the state, controlling the distribution of power through the production of carefully designed films, photographs, maps, and records. Media produced by infrastructural agencies, in other words, works to fuel the terraformation of the landscape while simultaneously changing the way its audiences perceive their environments and selves. As media subjects, dams and sprinklers are no longer only utilitarian objects; when aestheticized by the state, they become spectacular landscapes where dramas, comedies, and epics unfold. I assemble an extensive archive of films, photographs, texts, and other government-produced communications to underscore how infrastructure works as a cultural mediator between humans and the environment, shaping settler colonial narratives of power and redefining human-generated divisions between race, class, and the nonhuman world. While government-produced media make the case for mega dams, highways, and reservoirs as matters of national interest, my research also considers alternative media from the Black American press, folk quilt collectives, architecture, poetry, photography, and film that contest and rewrite the meaning of these infrastructural endeavors
Reasoning in Different Languages: Exploring Emotional Resonance and Deliberative Processing in Foreign Language Effect
No full textThe Foreign Language Effect (FLE) describes differences in decision-making when using a foreign language compared to native tongue. Particularly, a foreign language enhances logical consistency and reduces emotional biases. Despite its significance, the underlying mechanisms remain unclear. Two hypotheses have been proposed: the deducted emotion hypothesis suggests that using a foreign language reduces emotional biases; the increased deliberation account promotes more systematic thinking and attributes FLE to the increased cognitive loads, particularly the strain on working memory. These mechanisms may function independently or interactively. This study disentangles their relative contributions by analyzing syllogistic reasoning performance in English monolinguals and Chinese-English bilinguals. Reasoning tasks varied in emotional context (neutral vs. emotional) and logical forms, including Modus Ponens (MP), Denial of Antecedent (DA), Affirmation of Consequent (AC), and Modus Tollens (MT). Typically, MP and MT require higher cognitive loads than DA and AC. With bilinguals showing higher accuracy than monolinguals on DA and AC, a trend for an interaction of reasoning form was observed, as compared to MP and MT, lending support for the increased deliberation account. There was also a trend for a larger difference between emotional and neutral items in English compared to Chinese for items with lower cognitive loads, lending support for the reduced emotion account. However, limited statistical power prevented the detection of significant interactions, and reasoning form did not exhibit a consistent impact on overall performance. These findings suggest that both emotional and cognitive factors contribute to FLE, but further research with larger samples is needed
Evaluating The Role of Lipid Metabolic Genes in Cd4+ And Cd8+ T Cell Function and Metabolism
No full textImbalanced effector and regulatory CD4+ T cell subsets drive many inflammatory diseases. These T cell subsets rely on distinct metabolic programs, modulation of which differentially affects T cell fate and function. Lipid metabolism is fundamental yet remains poorly understood across CD4+ T cell subsets. Therefore, we performed targeted in vivo CRISPR/Cas9 screens to identify lipid metabolism genes and phosphatidylinositol (PI) genes and pathways essential for T cell functions. These screens established mitochondrial fatty acid synthesis (mtFAS) genes Mecr, Mcat and Oxsm for lipid metabolism, and Pi4kb in PI metabolism as key metabolic regulators. First with the use of Mecrfl/fl; Cd4cre novel mouse line, MECR-deficient CD4+ T cells proliferated, differentiated, and survived less well than control T cells. T cells ultimately showed signs of mitochondrial stress and dysfunction in the absence of MECR. Importantly, MECR-deficient T cells exhibited fitness disadvantages and were less effective at driving disease in an in vivo model of inflammatory bowel disease (IBD). In addition, the treatment of PI4KB with an inhibitor led to decreased proliferation and effector function in proinflammatory T cells and a subsequent increase in anti-inflammatory Treg phenotypes with dysregulated glycolytic and oxidative metabolism. Thus, previously unknown MECR and PI4KB mediated metabolism broadly supports CD4+ and CD8+ T cell proliferation and survival. This study shows that previously unknown immunologic targets for cancer, inflammatory, and autoimmune diseases can be found using CRISPR/Cas9 screens focusing on lipid metabolism pathways and diverse lipid metabolic pathways control CD4+ and CD8+ T cell function in vitro and in vivo
Influenza and COVID-19 Symptom Burden and Trajectory: Observations from Household Transmission Studies
No full textInfections caused by the influenza and SARS-CoV-2 viruses impose a substantial burden on the United States population every year. Although the largest burden of acute viral respiratory illnesses is in the ambulatory population, symptom severity studies have focused largely on hospitalized patients. Thus, the full spectrum of acute respiratory viral illnesses remains understudied. This study conducted in-depth assessment of symptoms and virological measurements throughout the course of infection and allows us to gain a deeper understanding of disease characteristics and severity in the community setting. Vaccination decreased symptom severity and quickened the time to symptom alleviation. This study helps inform how changes in symptom severity post-vaccination may increase vaccine uptake by determining the impact of vaccination in mitigating symptoms, whether levels of infectiousness are associated with symptom severity and how they may aid in infection prevention, and comparisons of influenza and COVID-19 will show how these diseases progress and the burden they pose on the population
Encouraging Bayesian inference in a task that assesses 5- and 6-year-olds’ Backwards Blocking
No full textCausal reasoning is an important ability for learning how the world works. Yet, there is considerably less consensus among researchers and theorists about how children reason causally. Another issue concerns how children reason about multiple candidate causes; most studies on causal reasoning in children rely on two objects. Understanding how children reason about multiple candidate causes is important theoretically because it can provide greater insight into the processes that might support causal reasoning in the real world. One study that attempted to address both questions was Benton et al. (2023). While it is understood that there was a shift from Bayesian inference to associative learning as the information processing demands of the task increased (Benton et al., 2023), there’s still uncertainty regarding whether we can predispose them to rely on Bayesian inference under greater information-processing demands, given that researchers agree that Bayesian inference is a more rational strategy than associative learning?
The aim of the current study is to investigate whether manipulating the base rate, which signifies the likelihood of an object being a cause and is a key parameter in standard Bayesian models, can promote Bayesian reasoning tendencies among 5-6-year-old children. In our experiment and computational models, we introduced the base rate prior to demonstrating the complex events described in Benton et al. (2023), aiming to assess whether this intervention can increase the probability of children deviating from their default associative learning strategies in a Backwards-Blocking task, a retrospectively reevaluating task. This study shows that while base rate information can shape children’s causal judgments, their retrospective reasoning under complex conditions is best explained by associative learning rather than Bayesian inference