VictorJuiz/thesis huggingface dataset:
The intersection of childhood health environments and educational opportunity

Standardized test scores are the most common measure by which the United States evaluates its public school system. These test scores are also one of the primary mechanisms by which opportunity is distributed to students throughout the country. These practices continue despite the fact that researchers and policymakers know that social conditions have a large influence on test scores. This dissertation is comprised of three papers that use population-level data to examine the role of specific environmental health factors in explaining variation in national test scores. The first paper examines the role of the opioid crisis in disrupting third-grade achievement scores across U.S. counties. The second paper builds upon the first paper by investigating associations between the opioid crisis and learning rates for different groups of students. The third paper contributes a unique measure of health access by calculating the physician-to-child-population ratio for every school district in the country. This paper describes the distribution of physicians trained in pediatric care, describes the groups of students who are served by that distribution, and ultimately describes the link between the distribution and early childhood academic achievement. Together, these three papers suggest the importance of exploring non-educational factors when seeking to explain national variation in test scores.

Keywords: Education.
Advisor: reardon sean
Domingue Ben
Humphreys Keith
Investigating drivers of small cell lung cancer progression and metastasis

Most cancer patients die from the development of metastatic disease; however, the molecular mechanisms underlying metastatic progression remain poorly understood. Small cell lung cancer (SCLC) is a particularly metastatic disease in which tumor heterogeneity has hindered identification of many tumor drivers. Heterogeneity in SCLC is in part moderated by the Notch signaling pathway, and we found that modulating expression of the atypical Notch ligand DLL3 changes the balance of neuroendocrine and non-neuroendocrine cells within tumors. Furthermore, the transcription factor NFIB is a known driver of tumor growth and metastasis in SCLC, but the requirement for NFIB activity for tumor development has not been investigated in vivo. We developed conditional Nfib knockout mouse models of SCLC and found that NFIB contributes to tumor progression, but loss of NFIB does not prevent tumors from metastasizing using alternative mechanisms. We further identified the pioneer factor FOXA1 as a candidate NFIB-independent driver of SCLC. Our work shows the importance of identifying other drivers of SCLC progression and metastasis to fully understand the plasticity and heterogeneity of SCLC tumors

Keywords: Medicine.
Advisor: Sage Julien
Pollack Jonathan D.
Winslow Monte
Van Rechem Capucine
INVESTIGATING FLUID FLOW BEHAVIOR IN ENHANCED GEOTHERMAL SYSTEM (EGS) WELLS: NUMERICAL AND DATA-DRIVEN APPROACHES

Enhanced Geothermal Systems (EGS) wells utilize artificial fractures created by stimulation to produce hot fluids. Understanding the fluid flow behavior within EGS wellbores is crucial for developing tools that can effectively measure the effectiveness of the fracture conduit in energy extraction over the well's lifespan.
This research contributed to a broader project, which combines analytical methods, numerical simulations, laboratory experiments, and field trials to create and utilize a chloride-based downhole tool. The tool is designed to identify feed zones and measure flow rates in Enhanced Geothermal Systems (EGS) wells through chloride concentration readings along the wellbore. Specifically, this research emphasized numerical simulation and data-driven analysis. The study utilized data and well configurations from the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) field, with the aim of applying the findings to other EGS sites.
Computational fluid dynamics techniques were employed to simulate fluid flow behavior within wellbores across various EGS configurations. Stochastic modeling and machine learning techniques were also utilized to estimate potential measurement errors and build a feed zone flow rate predictor. The results highlight several important phenomena, including blind spots in the mixing zone, downward volume distribution, and fluid flow path alterations caused by periodic turbulence. These findings emphasize the need to consider these factors when designing effective measurement tools. Moreover, simulations involving different tool positions suggest that chemical-based measurements are accurate primarily within the feed zone jet, potentially requiring correction if measured outside the jet. This indicates the importance of incorporating a centralizer in the wireline tool design.
Overall, this research provided insights into fluid flow behavior in EGS wells, reducing uncertainty in EGS well development. The study also proposed a practical tool design for measuring feed zone effectiveness that can be implemented in other EGS sites.

Keywords: Enhanced Geothermal Systems
Chloride ion
Downhole tool
Geothermal engineering
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Thesis
Advisor: Horne Roland
Investigating Gender Bias in Artificial Intelligence: The case of GPT

In the past decade, there has been rapid growth in the field of artificial intelligence (AI), with 2022 alone witnessing an investment of $91.9 billion in the private sector. This technological explosion, fueled by the advent of big data, computational power, and innovative methodologies, has not only amplified the efficiency, safety, and quality of work but also heralded an era of unprecedented innovation and economic progress. At the same time, the application of AI to complex problems in real-world situations raises many ethical concerns for policy makers and business leaders, including the presence of bias in AI systems and their consequent perpetuation thereof. This paper explores whether one of the most popular AI algorithms, OpenAI’s GPT, exhibits gender bias. The research compares GPT’s characterization of the typical gender of certain occupations with Bureau of Labor Statistics data on the actual gender composition of those occupations. The analysis for this paper showed that GPT did exhibit gender bias in 38 of the 50 occupations studied. This finding suggests that both researchers and policy officials might wish to give further attention to gender bias in AI systems and consider steps to mitigate that bias.

Keywords: Public Policy Program
artificial intelligence
bias
algorithmic gender bias
OpenAI's GPT
gender bias
gender bias in artificial intelligence
Stanford University
Humanities and Sciences
Public Policy Program
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Thesis
Advisor: Windham Patrick
Investigating genetic and cellular determinants of small cell lung cancer initiation and progression

Small cell lung cancer (SCLC) is a highly aggressive form of lung cancer with poor response to therapy. While the recent approval of immunotherapy as a first-line treatment for extensive-stage SCLC patients has improved patient survival, there still exists a dearth of targeted therapy options for SCLC patients. To better address SCLC progression and resistance to therapy, a greater molecular understanding of the disease is needed. To this end, we developed a higher-throughput method to screen for drivers of SCLC initiation and progression in in vivo settings. Using this method, we identified TSC1 as a strong tumor suppressor of SCLC and demonstrated potential therapeutic benefit of mTOR inhibition in patients with TSC1 alteration and/or patients that present with mixed SCLC/giant cell carcinoma histology. Among other drivers, we also identified ARID1A and ARID1B as oncogenes in SCLC, suggesting an important role for the SWI/SNF complex in modulating SCLC disease state. While cGRP+ pulmonary neuroendocrine cells have traditionally been thought to be the cell-of-origin for SCLC, recent experiments using mice with various genetic backgrounds and findings that non-neuroendocrine subtypes of SCLC exist have challenged that assumption. Because cell-of-origin has been shown influence the genetic mechanisms SCLC co-opts for progression and metastasis, we tested several cell-of-origin candidates such as PCSK1+ neuroendocrine cells, K5+ basal cells, TERT+ progenitor cells, and endothelial cells. We demonstrate that PCSK1+ neuroendocrine cells can serve as cell-of-origin for SCLC, while the other cell types provide potential models for several other histopathology, such as pancreatic islet hyperplasia, adrenal medullary hyperplasia, and angiosarcoma

Keywords: Medicine.
Advisor: Sage Julien
Khavari Paul A.
Rankin Erinn
Winslow Monte
Investigating impacts of heat stress on symbiosis in cnidarian larvae using high-throughput fluorescence-based quantification

Reef-building corals (phylum Cnidaria) exist in symbiotic relationships with photosynthetic dinoflagellate algae in the family Symbiodiniaceae. Under heat stress, corals lose these algal symbionts, resulting in a phenomenon known as coral bleaching. Due to rising seawater temperatures, more frequent bleaching events have led to significant degradation of coral-reef ecosystems worldwide. Much recent research has focused on whether the preferential association of adult coral polyps with thermotolerant species of algae improves resilience to bleaching. However, similar work on coral larvae has been limited. This study investigated the impacts of heat stress on the uptake and ejection of algae by cnidarians at the earliest stage of their life cycle, free-swimming larvae. Using the sea anemone Aiptasia as a model system, we addressed two questions ­– (1) the impact of heat stress on algal ejection by larvae populated with three different strains of algae of known thermal tolerances: SSA01, SSB01, and Mf2.2b (bleaching experiments) and (2) the impact of heat stress on symbiosis establishment in Aiptasia larvae with these three strains of algae (acquisition experiments). Uptake and ejection of algae by larvae were quantified using a novel high-throughput fluorescence-based sorting protocol employing the Union Biometrica BioSorter. Under control conditions in the bleaching experiments, Aiptasia larvae infected with SSA01 had the highest algal density, and in the acquisition experiments, larvae infected with SSB01 reached the highest algal density. The latter preference mimicked that of adults. Under heat stress, larval acquisition of algae was reduced across all three strains of algae; however, larvae that acquired SSA01 had higher algal densities than larvae exposed to the other two strains. Similarly, larvae already infected with SSA01 retained higher algal densities and even displayed proliferation of algae upon exposure to heat stress, compared to larvae infected with SSB01 or Mf2.2b. These results are surprising as Mf2.2b has been characterized before to be the most thermally tolerant algal strain in culture and in corals, followed by SSA01 and SSB01. One possible explanation might be that, unlike Mf2.2b, SSA01 and SSB01 are the native symbionts found in the male and female parent strains, respectively, with SSA01 being the more thermally tolerant of these two strains. This study is the first to investigate algal preferences in cnidarian larvae under heat stress at a high-throughput scale, and it provides new insights into the relatively understudied early life stage of cnidarians.

Keywords: Pringle, John
Coral bleaching, cnidarian-algal symbiosis, heat stress, cnidarian larvae
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Thesis
Advisor: Renicke Christian
Long Sharon
Investigating information framing with natural language processing

Words can influence both who and what we believe. Consider these headlines, which report on the same vaccine: "Moderna Vaccine Proves 96\% Effective in Teens," "Moderna Vaccine Highly Effective in Adolescents, Company Says." The first presents the efficacy as an established fact, while the second presents the efficacy as an assertion made by its manufacturer. Word choice regarding how assertions are made also matters: a company's "findings" (with semi-factive "find") strengthens the validity of its assertions, while a politician's "admission" carries negative connotations about their trustworthiness. Prior work studying information framing, or discourse acts in which a writer or speaker signals their stance with respect to a proposition from some source entity, has been restricted to a relatively narrow set of framing strategies over small-scale datasets. As a result, we know little about systematic patterns in information framing within real world contexts, and even less about its downstream effects on people's beliefs. In my dissertation I combine methods from linguistics, social psychology, and natural language processing (NLP) to study information framing in a data-driven way. In my first series of studies, I use my tools to discover linguistic strategies for conveying trust and doubt and I expose partisan patterns in how journalists exploit information framing to cover scientific issues. Next, I quantitatively measure the persuasiveness of framing strategies in social media arguments and reveal an interaction between epistemic commitment and politeness: high commitment is viewed as face-threatening and less persuasive when framing personal opinions, but has no effect on persuasion when framing scientific evidence. Finally, I conduct behavioral experiments to study the effect of information framing on attitude formation. I show that presenting information as opinions using non-factive verbs (e.g., "Scientists believe climate change is a serious concern") can affect what readers think is true, and to a greater extent, whether they think a ground truth exists in the first place. Together, this work contributes to our understanding of the role of language in how people form, update, and spread their beliefs, and contributes tools and datasets that may be applied to public interest messaging, conflict resolution and negotiation, and bias and misinformation detection systems.

Keywords: Humanities and Sciences.
Linguistics.
Advisor: Jurafsky Dan
Levin Beth
Knutson Brian
Investigating regulatory mechanisms of T cell effector function

T cells play an important role in recognizing and eliminating malignant cells, as well as providing protection from infectious pathogens. Multiple therapeutic modalities including vaccination, immune checkpoint blockade, and adoptive T cell therapy depend on robust T cell responses. Tumor microenvironments are often characterized by local immunosuppression and decreased T cell effector function. Consequently, increasing T cell effector activity in tumors is a common objective for the development of cancer therapeutics. Conversely, autoimmune disease progression is mediated by an imbalanced effector and regulatory immune response, prompting development of therapeutics to diminish T cell effector activity. Therefore, regulatory mechanisms that control differentiation and function of T cells are relevant for applications in medicine. In this dissertation, I will describe our work to identify regulators of T cell effector function. This question is first addressed in the context of cancer using a model system that mimics chronic antigen exposure to induce T cell dysfunction. Using genome-wide CRISPR screening, we identify the Meditator kinase module as a novel regulator of T cell function. We demonstrate this finding can be leveraged through genetic engineering and pharmacological approaches to augment T cell anti-tumor activity. This study further implicates interactions between the kinase module and core Mediator as a major axis of regulation of T cell differentiation. Technologies to inactivate genes are increasingly available for emerging applications in human medicine highlighting the potential for clinical translation of these findings. In the final chapter of this dissertation, I investigate the expression of immunomodulatory receptors in T cells isolated from patients with autoimmune disease. We identify receptors that are differentially expressed between effector and regulatory T cell subsets, providing a basis for selectively targeting effector T cells while preserving the function of regulatory T cells. Collectively, these studies explore multiple mechanisms to enhance or diminish T cell effector responses, providing new avenues for development of T cell directed therapeutics

Keywords: Medicine.
Advisor: Mackall Crystal
Engleman Edgar G.
Majzner Robbie
Satpathy Ansuman
Investigating the functional effects of enhanced glucose metabolism in T cells with chimeric antigen receptors

The combination of intensive nutrient requirements needed to sustain T cell activation and proliferation, alongside competition for nutrients within the tumor microenvironment suggest that glucose availability could limit CAR T cell function. Here we sought to test the hypothesis that stable overexpression (OE) of the glucose transporter GLUT1 in primary human CAR-T cells would improve function and antitumor potency. We observed that GLUT1OE CAR T cells manifest increased glucose uptake at rest and following activation, and this is associated with increased glycolysis and oxidative phosphorylation. In addition, GLUT1OE also enhanced MTOR signaling and broadly modulated metabolic programming, with substantial increases in glutathione mediated resistance to reactive oxygen species, and enhanced urea cycle and arginine metabolism. We observed no evidence for increased T cell exhaustion with GLUT1OE, but rather observed increased TCF1+ and CD62L, consistent with stemness programming. GLUT1OE CAR T cells showed increased cytokine production in response to tumor challenge and manifested superior tumor control in vivo. Our collective findings support a model wherein glucose availability is rate limiting for optimal effector CAR-T cell function and demonstrate that enhancing glucose availability via GLUT1 OE provides a new approach to augment antitumor immune function.

Keywords: Medicine.
Advisor: Mackall Crystal
Bendall Sean
Bollyky Paul
Majzner Robbie
Meyer Everett
Investigating the Immunogenicity of CBFA2T3-GLIS2 Positive Pediatric Acute Megakaryoblastic Leukemia for an Engineered T Cell Immunotherapy

The CBFA2T3-GLIS2 fusion oncogene is found in 18.4% of non-Down syndrome (DS) acute megakaryoblastic leukemia (AMKL) patients and is the oncogenic driver. These patients have the worst prognosis of acute myeloid leukemia patients (AML), having only a 14% overall survival, even with current treatments of chemotherapy and hematopoietic stem cell transplantation. These poor treatment outcomes highlight the need for novel therapies for AMKL. Recent novel therapies in other cancers engineer the immune system to target cancerous cells. These therapies include monoclonal antibodies, chimeric antigen receptor T-cell (CAR-T), and engineered T-cell receptor T-cell (TCR-T) therapies that function by binding to tumor-specific or tumor-associated antigens and stimulating a cytotoxic immune response. However, in the context of AMKL, there are currently no immunotherapy options. To explore potential AMKL targetable antigens, we screened the surfaceome of CBFA2T3-GLIS2+ patient cells that were expanded in a patient-derived xenograft (PDX) murine model. We eluted peptides from surface HLA:peptide complexes and utilized mass spectrometry for immunopeptidomics analysis. We identified 242 total peptides, 141 of which were not found in the human ligand atlas, indicating these peptides are leukemia-specific and not presented on normal cells. Of particular interest, we found a peptide from the BMP2 protein, which we have shown contributes to CBFA2T3-GLIS2 driven enhanced self-renewal, and a peptide from the DDX3X protein, which has been reported immunogenic in melanoma.
In an additional PDX murine model, mice engrafted with patient AMKL cells received healthy donor peripheral blood mononuclear cells (PBMCs) from a 6/6 HLA class I match individual. We observed variable reduction in leukemic burden and found those with the most significant reduction also showed a decrease in TCR clonotype diversity, suggesting the healthy T cells underwent clonal expansion directed against leukemia antigens. The clonally expanded TCRs were cloned into expression vectors and will be overexpressed in human CD8+ T cells to test functional response against artificial antigen-presenting cells (aAPCs) presenting the aforementioned peptides of interest through tandem minigene (TMG) assays and peptide stimulation assays. The identification of AMKL- directed effector CD8+ T cells and their corresponding immunogenic antigens will contribute towards the development of an immunotherapy for AMKL to improve patient outcomes.

Keywords: Acute megakaryoblastic leukemia (AMKL)
Leukemia in children
Immunotherapy
T cells > Receptors
T cells > Therapeutic use
Proteomics
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Thesis
Advisor: Garfinkle Elizabeth
Barron Annelise
Hernandez-Lopez Rogelio
Gruber Tanja
Investigating the use of small molecule inhibitors for area-selective atomic layer deposition

Area-selective atomic layer deposition (AS-ALD) is a materials synthesis technique with the potential to support the production of featured materials with single-nanometer accuracy. Conventional AS-ALD has used pretreatment with organic self-assembled monolayers (SAMs) as a step to enable the controlled placement of a given ALD material by blocking film growth on certain areas of the substrate. However, SAM molecules are often on the length scale of many of the features being created and also can be challenging to volatilize. Research into low molecular-weight molecules that can inhibit growth while being compatible with high-volume manufacturing is therefore of interest. In line with this research is the need to understand the surface chemistry and interfacial phenomena that support the inhibitory performance of small molecule inhibitors (SMIs), with the final goal being to understand the best ways to control and prevent nucleation of ALD depending on the growth surface of interest. This thesis explores the potential of several small molecule inhibitors to support AS-ALD, and seeks to elucidate the functionalities that contribute to high-performance blocking

Keywords: Engineering.
Chemical Engineering.
Advisor: Bent Stacey
McIntyre Paul Cameron
Tarpeh William