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Weight Discrimination and Its Association with Cardiometabolic Health
No full textThe present study aimed to understand characteristics of weight discrimination (i.e., attributions, settings, domains) and their associations with cardiometabolic health, as defined by metabolic syndrome and its individual components as well as self-rated health (SRH), among adults with overweight and obesity from the All of Us research program (n = 46,994). Multiple linear and logistic regression analyses were used to model the associations between discrimination attribution (i.e., whether due to weight, another social identity, or both) and cardiometabolic health. The associations between scores on the Everyday Discrimination Scale as well as the Discrimination in Medical Settings Scale and cardiometabolic health were also examined. Structural equation modeling tested specific domains of discrimination within these scales that have been identified in the literature (disrespect and condescension, character-based discrimination and hostility, healthcare discrimination) and their associations with cardiometabolic health. Participants reporting weight discrimination in addition to other forms of discrimination had greater odds of meeting criteria for metabolic syndrome than those reporting no discrimination (OR = 1.17, 95% CI [1.01, 1.35], p = .04). Weight discrimination, whether alone or along with other forms of discrimination, was negatively associated with SRH. Independent of discrimination attribution, both everyday discrimination as well as discrimination in medical settings were positively associated with metabolic syndrome and negatively associated with SRH. Confirmatory factor analysis showed that three distinct domains of discrimination fit the data best. Among the three discrimination domains, only healthcare discrimination was associated with lower SRH. These results underscore the importance of considering the heterogeneity of discrimination experiences due to weight, including how discrimination attributions and the setting of discrimination may be associated with cardiometabolic health. </p
Cultural Values and Treatment Outcomes among Hispanic Prostate Cancer Survivors in a Culturally Adapted Cognitive Behavioral Stress Management Intervention
No full textHispanic prostate cancer (PC) survivors experience significant disparities in health-related quality of life (HRQoL) compared to non-Hispanic White men. Despite high survival rates, PC treatment can lead to urinary and sexual dysfunction, pain, fatigue, and psychosocial challenges that impact HRQoL for years after diagnosis. Cognitive Behavioral Stress Management (CBSM) interventions have shown efficacy in improving HRQoL among cancer survivors, but limited research has explored how factors related to Hispanic culture influence treatment response.This study examined whether Hispanic cultural variables moderated the effects of a culturally adapted CBSM intervention (C-CBSM) compared to standard CBSM on HRQoL outcomes among Hispanic PC survivors. The sample consisted of 188 Hispanic PC survivors (mean age = 65.77 years, SD = 8.0) who had completed surgical (78.2%) or radiation (21.8%) treatment. Participants were randomized to either C-CBSM (n = 100) or standard CBSM (n = 88) delivered in Spanish over 10 weekly sessions. Multilevel modeling assessed intervention effects on general HRQoL and disease-specific HRQoL.Results revealed no statistically significant differences between conditions in direct effects. However, C-CBSM showed clinically meaningful improvements in overall HRQoL (4.09 points) exceeding the minimal clinically important difference threshold of 4 points, while standard CBSM did not (1.37 points). Moderation analyses revealed significant effects for simpatía on total well-being (b = 1.78, p = .005) and machismo on functional well-being (b = -0.40, p = .002). High-simpatía participants showed substantial improvements in C-CBSM (25-point increase) but declined in standard CBSM. Low-machismo participants improved in C-CBSM while high-machismo participants improved with standard CBSM. These findings challenge assumptions that cultural adaptation is universally beneficial, suggesting treatment response varies based on individual cultural profiles.</p
The Influence of Public Relations on Public Perception of Forever Chemicals in Response to the Release of the Film “Dark Waters”
No full textConcerns about the health consequences of industrial pollution have been steadily rising, particularly regarding per- and poly-fluoroalkyl substances (PFAS), commonly known as "forever chemicals." Historically, films have influenced public discourse on such environmental issues, bringing widespread attention to the dangers of toxic industrial practices. This thesis presents a qualitative content analysis of the public relations efforts surrounding the release of the 2019 film Dark Waters and their influence on public discourse and regulatory action related to PFAS. The study explores two intersecting PR strategies: the filmmakers’ advocacy-driven communication campaign, which was inductively coded to identify emergent themes, and DuPont’s crisis communication response, analyzed through the lens of Situational Crisis Communication Theory (SCCT). The research findings suggest that the PR efforts significantly influenced public discourse, contributing to increased media coverage, grassroots activism, and regulatory scrutiny of PFAS. This research underscores the role of strategic communication in shaping environmental narratives and driving policy change. </p
Particulate Matter Sensing and Characterization in Occupational Environments
No full textIncreasing knowledge about the health impacts of particulate matter (PM) air pollutants resulted in the widespread development and use of compact low-cost particulate matter sensors that have enabled spatially dense and high temporal resolution measurements. These PM sensors are advantageous due to their small size, lightweight design, affordability, and ability to connect to the internet for real-time data analysis. Most of these sensors operate on the principle of light scattering and require calibration based on the environment in which they are deployed. While there is a proliferation of such sensors, the performance over a wide range of particle properties needs to be firmly established. To the best of my knowledge, the current market (2025) has no commercial portable particulate matter sensor that can provide particle composition properties. The chemical, biological composition of a particle directly influences its refractive index. The refractive index of the particles plays an important role in establishing the inversion algorithms for accurate determination of PM concentration levels. In addition, not being able to determine the composition limits our understanding of how particulate matter affects the health and safety of humans in different occupational environments on a real-time scale. This dissertation focuses on the real-time measurement of particulate matter exposure and characterization of particles in occupational environments such as healthcare, orchestra, firefighting environments by utilizing a network of calibrated low-cost PM sensors complemented by research grade reference aerosol instruments for particle characterization. Furthermore, a novel multi-wavelength multi-angle optical sensor prototype using light scattering theory was developed to determine the refractive index of particles in addition to size and number concentration.</p
Stress, Racism, and Resilience: The Role of Racism-Related Stress and Coping on Cardiovascular Functioning of Young Black Women
No full textCardiovascular disease (CVD) is the leading cause of death in the United States, with persistent racial–ethnic disparities disproportionately burdening Black communities. This cross-sectional study examined the relationships between general stress, racism-related stress, coping, and cardiovascular functioning in a sample of 38 Black emerging adult women (ages 18-29), a period before the typical onset of clinical CVD. Participants completed measures of perceived stress, racism-related stress, and coping. Cardiovascular functioning was assessed via estimated cardiorespiratory fitness (VO₂ max) and carotid-femoral pulse wave velocity (cfPWV), a gold-standard measure of arterial stiffness. Results indicated that participants exhibited superior vascular health, with cfPWV values significantly lower than the U.S. and worldwide age-specific means. Participants reported moderate general stress, primarily from feeling “Pushed,” and indicated that their most frequent and stressful racism-related experiences were collective and vicarious. Spirituality was the most endorsed coping strategy, whereas Disengagement was the least used. Regression analyses revealed no significant direct relationships between psychosocial stressors and cardiovascular functioning. This null finding, interpreted through a life-course perspective, suggests that the physiological wear and tear of chronic stress is not yet detectable in this young, resilient cohort and provides a critical empirical baseline consistent with models such as the Weathering Hypothesis. The substantial proportion of variance explained in some models (R² = .21 for arterial stiffness) alongside an ambiguous finding for Interconnectedness coping indicates underlying complex, likely indirect pathways. Future research requires longitudinal designs and larger samples to test sophisticated models, as well as the inclusion of Black men to elucidate how psychosocial stressors translate into the cardiovascular health inequities observed later in life
Examining Obesity in African American Families Through a Social Environmental Lens: A Comprehensive Analysis
No full textIntroduction:African American (AA) women and families experience disproportionately high obesity rates, with 55.9% of AA women aged 20+ classified as obese. Despite evidence supporting family-centered approaches, the influence of the family social environment on obesity in AA families remains unclear. This dissertation aimed to: (1) review the role of the social environment on obesity in AA families; (2) validate the Family Health Scale (FHS) in a subsample of AA families; and (3) examine the predictive power of family health on BMI and obesity.Methods:Aim 1 used a scoping review of 14 studies (2014–2024) examining obesity and social environmental factors among AA families. Aim 2 used 2020 FHS Study data to conduct exploratory and confirmatory factor analyses assessing reliability and measurement invariance across racial groups. Aim 3 employed multivariate and logistic regression to test associations between FHS subscales and BMI in the full sample and AA subsample, adjusting for sociodemographic variables.Results:The review showed that AA family health and obesity are shaped by sociohistorical context. Aim 2 supported a four-factor FHS structure. Aim 3 found an inverse relationship between family health and BMI, highlighting the role of family dynamics in weight outcomes.Discussion/Conclusions:Results confirm the FHS as a reliable, multidimensional tool capturing social, emotional, lifestyle, resource, and support factors within families. Subscales were positively correlated, and the model demonstrated strong fit and cross-group equivalence.Implications:Validated tools like the FHS can strengthen research on social determinants, guide targeted family-centered interventions, and inform future longitudinal and cross-group studies to improve family health and obesity outcomes
Graph Neural Networks and Uncertainty Estimation in Healthcare: Advancing Patient-Specific Clinical Predictions
No full textDiverse clinical data, encompassing electronic health records, genomic profiles, and medical imaging, encode complex relationships between clinical variables, patients, and outcomes. Graph-based learning provides a natural framework for modeling these relationships, but effective representation learning in the face of data heterogeneity and the need of reliable uncertainty estimates for high-stakes clinical predictions remain open challenges. This dissertation develops a novel machine learning framework that integrates graph neural networks for relational modeling, multimodal learning for comprehensive data fusion, and Gaussian process-based uncertainty estimation for reliable predictions across two critical clinical tasks: sepsis onset prediction and breast cancer molecular subtype classification. This framework employs multimodal learning strategies to fuse information beyond structured EHRs, including temporal and relational dependencies from the MIMIC-IV dataset for sepsis and clinical, multi-omics, and imaging data for breast cancer. Spectral-normalized graph transformer convolution layers extract structured representations, while a random feature-based Gaussian process layer captures and quantifies predictive uncertainty. Integrated gradients provide interpretable attributions across temporal features, offering insight into global and patient-level prediction drivers. Uncertainty-aware modeling enhances reliability, providing well-calibrated confidence estimates that support clinical decision-making. This research demonstrates that the novel combination of graph-based learning, multimodal data fusion, and uncertainty estimation significantly improves predictive modeling in healthcare by addressing key challenges in data integration, representation learning, and uncertainty quantification. Future work will explore scaling multimodal integration, improving real-time inference, and extending interpretability methods to support clinician-centered deployment.</p
Regulating CD8 T Cell Exhaustion via MiR-29a and Anti-PD-1
No full textCD8 T cells mediate protective immune responses. However, persisting antigens such as chronic viruses or tumors redirect CD8 T cell differentiation to a suboptimal state called exhaustion. Exhausted T cells (TEX) lose their ability to persist long-term and initiate functional memory responses. Checkpoint blockade temporarily restores effector functions, but reinvigoration is not long-lasting. We recently demonstrated that microRNA-29a (miR-29a) attenuates exhaustion and promotes progenitor TEX. Therefore, we hypothesized that miR-29a epigenetically re-directs TEX differentiation and synergizes with checkpoint blockade. Indeed, we found that miR-29a epigenetically altered TEX and resulted in the differentiation of durable, persisting progenitor TEX with increased effector function upon aPD-1 blockade. Thus, combining ectopic expression of miR-29a with aPD-1 promoted T cell stemness while enhancing functional effector responses. Together, we suggest that miR-29a epigenetically reprograms TEX and promotes long-term persisting, functional CD8 T cell responses in response to checkpoint inhibitors.We further investigated whether miR-29a modulated already differentiated TEX. Conditional overexpression of miR-29a at late stage of chronic infection promoted the expansion of progenitor-like T cells, and the phenotypic changes induced by miR-29a were stably maintained over time, suggesting that miR-29a has potential to rewire established TEX. To further explore the translational potential of miR-29a, an anti-PD-1-miR-29a conjugate was generated and shown to deliver miR-29a to PD-1+ T cell in vitro. Although the effects of the conjugate in vivo were modest, these findings provide a proof of concept that targeted miR-29a delivery may regulate TEX and represent a feasible approach for therapeutic development.Collectively, this dissertation elucidates how miR-29a and aPD-1 blockade cooperatively reprogram CD8 T cell exhaustion, offering mechanistic insight and translational potential for enhancing sustained anti-viral and anti-tumor immune responses
Applied Magnetics for Medical Devices from Magnetoelectric Nanoparticles to Macroscale Electromagnetic Devices
No full textMagnetoelectric nanoparticles (MENPs) are introduced as a platform for wireless medical intervention and neuromodulation. Magnetic methods avoid limitations of electrical stimulation in conductive tissues, where charge screening and attenuation restrict penetration and precision. By coupling magnetic and electric order, MENPs convert alternating magnetic fields into localized electric potentials at cell membranes, enabling deep signal penetration with external fields through the brain and body.We synthesize core-shell cobalt ferrite and barium titanate MENPs as a biocompatible composite material. The cobalt ferrite core supplies strong magnetostriction, while the barium titanate shell provides piezoelectric polarization and improves biocompatibility. Nanoscale dimensions support transport across biological barriers, notably the blood-brain barrier (BBB) and promote close contact with neurons to maximize the efficiency of the generated fields. We present fabrication, structural and functional characterization (crystallography, magnetic hysteresis, XRD, microscopy), and a multi-scale evaluation from primary neuronal cultures to rodent and non-human primate (NHP) models. Although synthesis remains under optimization, experiments show repeatable, wireless neural activation with externally applied magnetic fields, validating MENPs as nanoscale receivers for wireless localized neurostimulation. We also report preliminary studies indicating targeted ablation of cancer cells in mice via magnetoelectrically mediated mechanisms, suggesting minimally invasive oncology applications. Finally, we outline theory and device concepts for MENP-assisted neural recording, establishing benchmarks and design criteria for next-generation magnetoelectric brain-machine interfaces.</p
Atomic Layer Deposition for Efficient, Stable, and Scalable Perovskite Solar Cells
No full textSolar energy has emerged as a promising renewable energy source, drawing significant attention worldwide. Among various photovoltaic materials, perovskite (PVK) stands out as one of the most promising candidates for solar energy harvesting. My research focuses on optimizing high-performance perovskite solar cells (PSCs) by addressing key challenges to industrialization through innovative material design and process engineering. My key contributions are as follows: 1. Hole Transport Layer (HTL) Innovation: I developed a dual-oxidant atomic layer deposition (ALD) technique using ozone and water to fabricate high-quality films. This approach enables high reaction rates and controlled surface hydroxylation, resulting in PSCs that achieve 21.2% efficiency and maintain 80% of their initial performance after 500 hours of continuous light soaking. 2. Blade Coating and Additive Engineering in Ambient Conditions: I optimized the blade coating process and vacuum-assisted quenching under ambient conditions. Additionally, the introduction of as a chloride-based additive significantly reduced trap-state density and extended carrier lifetime. This enabled the fabrication of PSCs with 23.9% efficiency and mini modules reaching 18.0%. By integrating synergistic ALD processing, blade coating techniques and chloride additive incorporation, this work significantly improves both the efficiency and operational stability of PSCs. These results lay a strong foundation for the scalable, low-cost manufacturing of high-performance perovskite photovoltaics.</p