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Psychedelics, Cannabis, and Cancer: Prevalence, Association, and Trends from 2015-2022, Using a Nationally Representative Dataset of United States Older Adults
No full textClassic psychedelics and cannabis are at the forefront of emerging alternative therapies to mitigate cancer symptoms and comorbidities, yet their prevalence, patterns, and long-term effects among older adults remain unclear. This dissertation utilizes 2015–2022 National Survey on Drug Use and Health data to 1) examine trends in lifetime cannabis and psychedelic use among US adults aged ≥50 years, 2) assess variations by cancer history and type, and 3) investigate potential associations with prostate cancer.The first study estimates prevalence and trends in classic psychedelic, cannabis, and combined use (co-use) among adults with past, recent, or no cancer history, considering socio-demographics. Findings show increasing use, particularly among adults ≥65 and males, highlighting the need for further research into therapeutic intent, usage patterns, and integration into cancer care. The second study examines the prevalence of cannabis, classic psychedelic, and co-use among cancer patients by cancer type. Findings show similar cannabis use in cancer survivors (41.6%) and non-cancer individuals (42.6%, p=0.21), but lower psychedelic (11.6% vs. 12.9%, pThis dissertation is the first in the literature to report rising cannabis and psychedelic use among a population-based sample of older US cancer patients, highlighting type-specific trends and links to prostate cancer.</p
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
Trajectories and Predictors of Alliance in an Online Relationship Intervention
No full textIn both individual and couple therapy, the therapeutic alliance explains approximately 7% of the variance in treatment outcomes. Existing evidence indicates that the alliance remains a key predictor of outcomes in teletherapy and even digital-first interventions for individuals. Research on alliance in digital interventions with couples is limited, but some studies show its importance in these contexts as well. However, trajectories of alliance in digital-first interventions for couples, as well as predictors of alliance in digital interventions for both individuals and couples, remain underexamined. This study involved a sample of 298 couples enrolled in the OurRelationship program, an online intervention for low-income couples supported by brief coach calls. It used a multi-level modeling framework to examine two aims: (1) coach alliance means, variability, and slopes and (2) predictors of the strength and slopes of alliance. Specifically, gender, psychological distress, conflict, emotional trust, and relationship satisfaction were explored as predictors, as these have been shown to influence alliance in other service delivery formats. Aim 1 analyses revealed that alliance ratings were positive, with a mean alliance of 8.97 for men and 9.37 for women, and it grew over time even when controlling for the effect of program completion. Linear modeling of the effect of time fit the data better than nonlinear modeling. Aim 2 results revealed that gender, emotional trust, and relationship satisfaction predicted mean alliance, whereas distress and conflict did not. No variables significantly predicted the rate of change of alliance over time, and there was no evidence of gender moderating any predictors. The findings suggest that positive alliances do form in online couple interventions and that they grow over time, replicating extant literature in couple therapy. They also emphasize the importance for practitioners to intentionally foster alliances with male partners and with couples experiencing low levels of trust or relationship satisfaction.</p
ABCDs: Argentina, Bolivia, Courts, and Democracy
No full textThis research considers Argentina and Bolivia as exemplary case studies of how political court-packing, and the subsequently diminished rule of law, have eroded democratic safeguards.The purpose of an independent judiciary is not to be redundant on the legislative or the executive, but to be a guardrail. A democratized judiciary that is highly responsive to political whims is vulnerable to the institutional deterioration of unchecked populism, not a check on it. If we care about protecting democracy, we should also protect the independence of our courts to uphold the rule of law (at home, and throughout our hemisphere). Systemic attacks, including assaults on the integrity and personal safety of jurists, undercut judiciaries throughout our hemisphere and threaten critical norms and safeguards of liberal democracy.Sadly, the plague of this dangerous and erosive politics is not only limited to solely deteriorating the tissue of judicial integrity, but it also breeds corruption and enables political unaccountability. Efforts by dictators (and their authoritarian aspirants, alike) to weaken institutional norms and disable anti-authoritarian mechanisms have included coercion, threats, and court-packing — all to stifle the rule of law. Argentina’s Cristina Fernández de Kirchner and Bolivia’s Evo Morales have made these (and other) attacks against their national judiciaries; they have sought to reshape their judiciaries in Argentina and Bolivia into “kangarooed” rubber-stamps favoring their personal and partisan interests. Courts have been incapacitated to check or balance the authority of the other branches and have been contorted into complicity in abuses of power, infringing on due process and fundamental rights, and legislating from the bench.Kirchner’s and Morales’ forays into “court-packing” and other so-called judicial “reforms” provide case-studies and warnings of the potential consequences to democratic stability in our hemisphere if similar efforts to politicize, or otherwise erode, judicial independence are adopted.</p
Tandem Repeat Variation in Human Genomes and Its Role in Health and Disease: Insights from Long-Read Sequencing
No full textUnderstanding the genetic basis of both rare and common diseases remains a major challenge. Despite advances in genomics, over half of individuals with rare diseases still lack a genetic diagnosis. This diagnostic gap suggests that conventional approaches may miss complex or unconventional forms of variation, such as tandem repeats (TRs)—sequences of repeated DNA motifs that vary in structure and length.TRs are highly mutable and historically dismissed as "junk DNA," yet they are now implicated in over 60 rare diseases, including Fragile X syndrome and Huntington’s disease. Increasing evidence also suggests that TRs regulate gene expression and have biological function. However, due to the limitations of short-read sequencing, the variability and clinical relevance of most TRs remain poorly characterized. With the advent of long-read sequencing, it is now possible to study these regions at high resolution and scale. In this dissertation, I analyze TR variation across more than 1,000 long-read human genomes from the All of Us Research Program, aiming to map TR polymorphism and investigate its roles in disease.To do this, I built a population-scale control database of TRs and developed novel computational tools for analyzing their genetic and functional complexity. Using TRGT, I generated high-resolution TR genotypes from PacBio HiFi data and benchmarked them against short-read ExpansionHunter calls. I profiled known pathogenic loci and compared them to non-pathogenic loci, developing new methods to decompose, visualize, and quantify TR sequence structure. These tools enabled discoveries in non-coding pentanucleotide TRs, an emerging class of pathogenic variation.Together, these findings provide foundational resources and insights for the study of tandem repeats in rare disease, common traits, and human evolution. </p
Phosphatidylserine Decarboxylase and Its Effects on Retinal Ganglion Cell Axonal Growth and Lipidomics
No full textOptic neuropathies lead to irreversible blindness that cannot be restored through current therapeutic interventions. Optic neuropathies result from damaged retinal ganglion cell (RGCs) axons that transmit the visual signal from the eye to the brain. Human glaucomatous optic nerves tissues present an aberrant accumulation of phosphatidylethanolamine (PE) by upregulated phosphatidylserine decarboxylase (PSD) expression and activity. PSD is a cristae-localized, mitochondrial enzyme that converts phosphatidylserine to PE. Concurrently, glaucomatous mouse models present short, spherical mitochondrial morphologies lacking cristae curvature. The relationship between PSD and RGC mitochondrial morphologies has not been studied. Optic nerve regeneration is a promising avenue for restoring lost vision. Regenerative optic nerve lipidomic profiles display reduced PE while regenerating RGC transcriptomics reveal downregulated PSD expression.This work evaluates PSD’s effects on RGC axonal growth, mitochondrial morphology, membrane fluidics by C-Laurdan, and lipidomics. We utilized AAV2-mediated gene modulation using C57BL/6 mouse RGCs in vitro and in vivo. PSD overexpression (PSDOE) and PSD knockdown (PSDKD) by three separate shRNAs (sh1, sh2, sh3) were assessed in stimulating RGC neurite outgrowth in vitro. Overall, PSDKD (PSDsh3) significantly increased RGC neurite outgrowth with minimal effects on mitochondrial morphology. PSDKD significantly increased somal membrane fluidity accompanied by lipid profiles presenting reduced cholesterol phosphatidylcholine, and saturated triacylglycerols. In contrast, PSDOE presented the shortest neurite outgrowth and short, spherical mitochondria. Using 2 month old C57BL/6 mice and in vivo optic nerve crush model, PSDKD by PSDsh3 significantly increased mCherry+CTB+ short-distance regenerating axons (<200µm). These results indicate that PSDKD stimulates RGC axon regenerative competency and is likely a good candidate for combinative therapies for long-distance regeneration.</p
Integrating Cathodic Protection and Energy Storage in Concrete: A Multifunctional Zn-Cement Anode for Durable and Electrochemically Active Infrastructure
No full textConcrete infrastructures face two major challenges: protecting embedded steel from corrosion and enabling multifunctional capabilities such as energy storage. Achieving durable reinforcement protection is essential for structural longevity, while integrating electrochemical functionality can transform concrete into an active component that supports low-carbon, smart infrastructure. Existing corrosion-mitigation methods and concrete batteries often compromise structural integrity or suffer from limited lifetime and low power output.In this study, a discrete Zn-embedded cement-based anode (DZCA) and a Zn-anode rebar-reinforced cementitious battery (ZARCB) were developed to provide both cathodic protection and energy-storage capability. The DZCA acts as a sacrificial anode and the embedded rebar serves as the cathode, eliminating external electrodes and maintaining structural integrity. Performance was enhanced through increased electrolyte alkalinity, porosity optimization, biochar-induced pore regulation, and a PVA-hydrogel coating that improved ionic connectivity and interfacial stability.Long-term durability was evaluated under simulated field stressors including chloride exposure and cyclic wet–dry conditions. High-alkalinity systems (>5 M KOH) provided superior corrosion protection, while the 5 M condition delivered the most stable microwatt-level energy output. Porosity optimization revealed a trade-off in which moderate porosity (9.1–11.6%) ensured stable long-term performance. Biochar addition buffered electrolyte fluctuations and sustained activity, and the hydrogel coating further enhanced stability and power delivery.These results demonstrate that rational design of composition and microstructure can significantly improve the durability and multifunctionality of cement-based electrochemical systems. DZCAs offer a promising route toward self-sustaining, corrosion-resistant, and energy-integrated concrete infrastructures
Leveraging Machine Learning Techniques to Accelerate Material Innovation in Civil Engineering Applications
No full textMany persistent challenges in civil and environmental engineering require innovative materials—such as creep-resistant cement for structural durability, materials that incorporate CO₂ into building components, and low-cost catalysts for water treatment. Traditional materials discovery is slow and costly, relying on trial-and-error. While physics-based computational methods improve understanding, they are resource-intensive and unsuited for high-throughput screening. Machine learning (ML) offers a powerful alternative, enabling efficient exploration of material properties and recognition of patterns beyond human capability.This thesis applies ML techniques to accelerate material innovation across three key areas:I. Creep Prediction in Disordered Solids: Using molecular dynamics and ML classification, we identify "looseness", a structural descriptor strongly correlated with early-stage creep in calcium-silicate-hydrate (C-S-H), guiding microstructural design.II. High-Entropy Alloy (HEA) Electrocatalysts: ML regression models trained on DFT data predict O* and HO* adsorption on CoFeNi-X (X = Mo, Mn, Cr) HEAs, enabling rapid screening and design for water treatment catalysts.III. Earth-Abundant Oxides for CO₂ Mineralization: Pre-trained ML models from the Open Catalyst Project are used to screen CO₂ adsorption on 21 metal oxides. MnO (2, -1, 2) and Ti₂O (1, 1, 0) with oxygen vacancies emerge as promising catalysts.By integrating ML with simulations and open databases, this thesis establishes predictive frameworks for rational material design, supporting advances in civil engineering and sustainable technologies.</p
Informant Discrepancies in the Treatment of Youth Internalizing Disorders: Implications for Clinical Outcomes and the Effect of Measurement-Based Care
No full text The integration of evidence-based assessment practices in treatment has been shown to enhance clinical outcomes for youth, however discrepancies in the views of youth and parents on the presence, severity, and effects of youth psychopathology often complicate the treatment process. Measurement-based care (MBC), the routine collection, evaluation, and sharing of assessment data to monitor and support treatment progress, may promote the alignment of varied perspectives. This study sought to further understand the link between parent-youth informant discrepancies and youth treatment outcomes and the potential moderating effects of engagement in and dosage of measurement-based care. Participants included 196 parent-youth dyads, with youth ages 12 to 18. Informants completed ratings of anxiety, depression, and overall symptom severity at the outset and throughout treatment, and youth clinical outcomes were assessed at multiple timepoints. Two of the three treatment conditions incorporated MBC and clinicians within these conditions reported on their MBC practices at each session. Hierarchical linear and logistic modeling using polynomial regression was used to examine the proposed models. Exploratory analyses were also conducted to assess descriptive changes in parent-youth discrepancies on symptom measures over the course of treatment. Results showed that youth reported significantly greater anxiety symptoms than parents at baseline and greater depressive symptoms than parents at the 8-week timepoint. Greater pre-treatment parent-youth discrepancies in anxiety ratings were found to predict a lower likelihood of treatment response at the 16-week timepoint. Engagement in and dosage of measurement-based care were not found to moderate associations between pre-treatment discrepancies and youth treatment outcomes. Exploratory analyses revealed descriptive trends of increased concordance in average symptom ratings over the course of treatment for anxiety measures across conditions, for those who received MBC, and for those who were treatment responders.</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