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Wayfinding: Searching for hints of new physics using a weakly-supervised anomaly search and a measurement of high- production with the ATLAS experiment
No full textEfforts to discover a convincing discrepancy between experimental results and the Standard Model of particle physics have, up to this point, been unsuccessful. However, the Standard Model is known to be incomplete, and many theories of physics beyond the Standard Model predict new physics at the TeV scale or higher. This thesis presents two analyses designed to aid the search for new physics using proton-proton collision data collected by the ATLAS experiment at the Large Hadron Collider.
The first, a weakly-supervised anomaly search in dijet events produced at a center-of-mass energy of \sqrt{s} = \SI{13}{TeV}, used novel machine learning techniques to search for resonances that clustered in high-dimensional phase space and manifested as bumps in the dijet invariant mass spectrum. The search was model-agnostic, insofar as it did not target any specific model of new physics and relied minimally on Standard Model simulation. No significant excess above the expected background was observed, though state-of-the-art limits were set on a wide variety of benchmark models. This analysis was the first weakly-supervised search in ATLAS to utilize more than one training feature, and the techniques developed in the search will provide a starting point for future anomaly searches.
The second analysis was a measurement of production in final states with two leptons at a center-of-mass energy of \sqrt{s} = \SI{13.6}{TeV}. The measurement targeted the region of phase space in which the top quarks were produced with high transverse momentum. The top quarks were reconstructed using a jet reclustering technique. The production rate was measured inclusively, and differentially in 9 observables chosen to maximize sensitivity to the Standard Model effective field theory. This measurement was the first measurement at \sqrt{s} = \SI{13.6}{TeV}, and the first to target the high- top quark regime. The inclusive measurement was found to be in agreement with the Standard Model prediction, but statistically-significant discrepancies were observed in the differential measurements. In particular, the boson was found to have higher momentum than expected, and the top quarks lower. The results were qualitatively consistent with previous global fits to the Standard Model effective field theory.Physic
Unraveling the molecular mechanisms of neuronal and astrocytic proteostasis in human models of Alzheimer’s disease
No full textCellular proteostasis is the integrated regulation of protein synthesis, folding, trafficking, and degradation that sustains the integrity of the proteome. By balancing these processes, cells preserve homeostasis under both basal conditions and during periods of physiological stress. This regulation is especially critical in post-mitotic cells such as neurons, as well as in other brain cell types including astrocytes. In the brain, disruption of the proteostasis network promotes the accumulation of misfolded or aggregated proteins that drive the pathogenesis of neurodegenerative disorders, including Alzheimer’s disease (AD). Of particular relevance to neurodegeneration is the degradation arm of proteostasis, as impairments in autophagy and proteasomal pathways result in the accumulation of toxic protein aggregates that are hallmarks of disease.
The autophagy-lysosome pathway (ALP) and the ubiquitin-proteasome system (UPS) represent the two major degradative mechanisms that sustain cellular proteostasis. Together, these systems form the core of the protein quality control network, ensuring the clearance of damaged, misfolded, or aggregated proteins, as well as dysfunctional organelles. While the UPS primarily targets short-lived soluble proteins, the ALP provides both bulk and selective degradation routes capable of removing larger protein aggregates and organelles, a particularly important process for mitigating the toxic effects of aggregation prone proteins in neurodegenerative diseases. While autophagy can be both a bulk and selective degradation process, selective autophagy itself depends on molecular chaperones and adaptor proteins that identify substrates and recruit them to degradative machinery. Dysfunction in these pathways has been strongly implicated in AD pathogenesis, highlighting the importance of understanding how some of these adaptor proteins and chaperones might regulate ALP activity and influence disease pathophysiology.
Optineurin (OPTN) is one such autophagy adaptor protein with established roles in selective autophagy. Pathogenic mutations in OPTN have been linked to amyotrophic lateral sclerosis, frontotemporal dementia, and glaucoma, but its contribution to AD and neuronal function remains unclear. To investigate the role of OPTN in neuronal proteostasis and AD, we utilized induced pluripotent stem cell (iPSC)-derived neuron (iN) and astrocyte (iA) models. Analyses revealed a negative correlation between OPTN and specific pTau epitopes in neurons, as well as a decrease in OPTN protein abundance in brain tissues of individuals with AD. Given these findings, we generated OPTN knockout (KO), heterozygous (HET), and wildtype (WT) iNs and iAs using CRISPR/Cas9 editing in two genetic backgrounds. Loss of OPTN in iNs increased specific pTau proteoforms without substantially affecting autophagy processes or mitochondrial respiration. Despite no clear effect on mitochondrial function, several mitochondrial proteins, including OXCT1, were enriched in an unbiased analysis of the OPTN interactome in iNs, as well as proteins involved in intracellular trafficking. Proteomic analyses further identified intracellular Clusterin (CLU), an AD risk gene, as significantly upregulated in OPTN KO iNs, suggesting OPTN may influence its intracellular processing. Our model system demonstrates modest roles for OPTN in certain neuronal biological processes and potential implications for AD pathogenesis. These findings also suggest that OPTN may exhibit functional redundancy with other autophagy adaptor proteins in human neurons, leading to relatively mild phenotypic changes with complete loss of OPTN.
Another important form of selective autophagy relevant to neurodegenerative disease is chaperone-assisted selective autophagy (CASA). Bcl-2-associated athanogene 3 (BAG3) is a mediator of CASA, and given the genetic and pathological links of BAG3 to proteostasis and neurodegenerative diseases, we investigated how BAG3 contributes to cellular function and Alzheimer's disease (AD) in both human neurons and astrocytes. We first utilized a large panel of iPSCs from deeply phenotyped cohorts to interrogate genetic contributions to baseline autophagic flux and UPS activity in human neurons, and protein turnover was assessed using SILAC-based quantitative proteomics. Across our panel of neurons, we observed substantial inter-individual differences in autophagic flux, which was inversely correlated with UPS activity. This reciprocal relationship extended to tau homeostasis, where higher autophagic flux resulted in reduced accumulation of aggregated, phosphorylated tau. Proteomic analyses revealed that global protein turnover dynamics stratified based on degradation pathway activity and could predict pathway-specific substrate dependencies. Interestingly, BAG3 emerged as a dynamically regulated autophagy chaperone, responsive to pharmacological inhibition of both the UPS and ALP. BAG3 knockout in neurons decreased autophagic flux and increased levels of high-molecular-weight phosphorylated tau. Notably, familial APP AD mutations and Aβ exposure induced BAG3 expression in neurons, while elevated BAG3 levels in human brain tissue were associated with higher neuropathological burden and disease progression.
While an elevation of BAG3 was observed in the AD brain, it was unclear which brain cell type might be contributing most to this upregulation. We found that in human brain and iPSC models, BAG3 was most highly expressed in astrocytes. Further, BAG3 loss in our iPSC model system caused greater proteomic disruption in astrocytes than in neurons. In the absence of BAG3, astrocytes showed reduced autophagy, diminished lysosome abundance and activity, and decreased proteasome function. To uncover molecular binding partners of BAG3 that might influence these phenotypes, we performed co-immunoprecipitation, revealing interactions with HSPB8 and other heat shock proteins, proteasome regulators (PSMD5, PSMF1), and the retromer component, VPS35. Integration of BAG3 KO transcriptomic and proteomic datasets pinpointed AD-relevant proteins under post-translational control of BAG3, which included GFAP, BIN1, and HSPB8. HSPB8 levels were markedly reduced in BAG3-deficient astrocytes with overexpression partially rescuing its levels. Loss of astrocytic BAG3 impaired Aβ clearance in co-culture with APP/PSEN1 mutant neurons, directly linking BAG3 to a disease-relevant astrocyte function. Finally, analysis of postmortem brain tissue revealed BAG3 marks a stress-responsive astrocyte subtype in the brain of aged individuals with AD.
Collectively, these studies define complementary and cell-type specific contributions of OPTN and BAG3 to proteostasis in the human brain and AD. They reveal how adaptor proteins and chaperones regulate neuronal and glial protein quality control, highlight BAG3 as a central regulator responsive to genetic and pathological stress, and establish mechanistic links between proteostasis dysfunction and AD pathogenesis. Together, this work advances our understanding of proteostasis networks in the brain and identifies potential therapeutic nodes within these pathways for combatting neurodegenerative disease.Biological and Biomedical Science
The Impact of Restorative Practices and Positive School Climate on Student Outcomes: Evidence from Santa Ana Unified School District (SAUSD)
Get PDFRestorative practices and positive school climate models have emerged as promising frameworks for addressing school disciplinary issues, while fostering students’ social-emotional learning. Restorative practices (RP) emphasize healing, accountability, and relationship-building, offering an alternative to exclusionary discipline. Similarly, the Enhanced Positive School Climate Model (EPSCM) integrates social-emotional learning (SEL) strategies, cultural responsiveness, and proactive climate strategies to promote inclusive school environments. This dissertation evaluates the effectiveness of these interventions in the Santa Ana Unified School District (SAUSD), a large, equity-focused district serving a majority-Latino student population.
This dissertation consists of two major studies. The first evaluates the effect of restorative practices and combines two papers I proposed for this dissertation: one focused on student behavior (e.g., student misbehavior and academic performance), and the other focused on school responses to misbehavior (e.g., school disciplinary practices). Using a quasi-experimental design, I analyze whether introducing RP reduces reliance on exclusionary discipline, affects student infractions, and influences school-level disciplinary responses. While the intervention had no statistically significant effect on academic or attendance outcomes, it did yield a statistically significant reduction in out-of-school suspensions, which is an important equity-relevant outcome. At the same time, reports of defiance and noncompliance increased, suggesting possible shifts in how misbehavior was categorized. These findings point to the complexities of adult adaptation to RP frameworks and the importance of implementation fidelity.
My second study assesses the impact of the EPSCM on students’ perceptions of school climate and SEL competencies. Using student survey data, I evaluate whether EPSCM improves students’ sense of safety, trust in school staff, and perceptions of fairness in disciplinary practices. My findings indicate no significant improvements in these measures compared to control schools. SEL outcomes, including self-management, growth mindset, and social awareness, show small positive effects, but they are statistically insignificant at traditional levels. These results suggest that while the EPSCM is conceptually aligned with fostering a positive school climate, its implementation did not yield measurable improvements over my study period.
These findings highlight the potential and limitations of restorative practices and enhanced positive school climate models in transforming school discipline and climate. While RP can reduce reliance on suspensions, its broader behavioral and academic impacts remain inconclusive. Similarly, EPSCM’s effectiveness in improving school climate and SEL outcomes warrants further investigation. My results underscore the challenges of implementing and evaluating large-scale school climate interventions and suggest the need for refinement to achieve their intended outcomes.Educatio
Educational Encounters: (Re)Writing Identity in Twentieth-Century Brazil and the U.S.
No full textThis dissertation investigates literary articulations of identity in twentieth-century Brazilian and U.S. fiction through representations of education. Focusing primarily on Afro-descendant and women authors—including James Weldon Johnson, Rachel de Queiroz, Romeu Crusoé, Ralph Ellison, Lygia Fagundes Telles, and Angela Jackson—I analyze how shifts in educational access during the 1910s–1970s influenced these writers’ portrayals of identity as something learned and performed. Central to this study is the argument that these authors employ education as a narrative strategy, revealing the ways in which identities are imposed, negotiated, resisted, and redefined. I propose two interpretive frameworks—“educational encounters” and “horizons of expectations”—to demonstrate how educational scenes elucidate the racialized, gendered, and classed assumptions that structure formal pursuits of knowledge. This dissertation adopts a transatlantic comparative lens, engaging with Robert Stam and Ella Shohat’s framework of “culture wars around the postcolonial Atlantic” to explore how universalist ideals—largely inherited from French philosophical and political traditions—persist and transform within Brazilian and U.S. literary contexts. By placing these authors in dialogue across national and linguistic boundaries, I illustrate how their work sheds light on ongoing philosophical and political debates about who has historically been permitted to represent the universal human subject, contrasted against who has been relegated to particularity. This dissertation also recovers Romeu Crusoé’s overlooked legacy within Afro-Brazilian literary history. By drawing on previously untapped biographical and archival research, I reconstruct Crusoé’s career and establish his central role in twentieth-century Afro-Brazilian literature.Comparative Literatur
Calligraphic Renaissance: From Gutenberg to Dürer
No full textThis dissertation recovers the world of Renaissance calligraphic art from 1450 to 1550. Through the work of calligraphic artists in Mainz, Augsburg, Nuremberg, Venice, and beyond—from Peter Schöffer’s collaboration with Johannes Gutenberg to Johann Neudörffer’s calligraphic innovations—it reveals how writing served as a vital site for artistic experimentation. Bookended by trials, the project interweaves historical narrative with “Writing Lessons” that reconstruct Renaissance pedagogical methods. These lessons move from elemental forms through systems of letter construction to Neudörffer’s transformation of both calligraphic pedagogy and art history, showing how the physical act of forming letters served as a crucial testing ground for theories of artistic practice, science, and human nature. The conceptual imbrication of writing and philosophy, and the practical ambiguity between writing and drawing, generated both technical innovation and theoretical reflection, while Neudörffer’s distinctive mode of etching achieved the immediacy that had eluded both Albrecht Dürer and Leonardo da Vinci. Throughout Europe, engagement with writing served as a catalyst for nascent constructions of personal and national identity across painting, drawing, manuscript, metalwork, sculpture, and printmaking, and from Gothic to Greek to Hebrew scripts. By recovering these overlooked connections—many drawn from previously neglected archival sources—this study traces calligraphy’s enduring influence. Its impact extends from the Carolingian reform through Renaissance, Protestant Reformation, Romantic, and early American experiments in artistic writing, fundamentally reshaping what it means to conceptualize and narrate the story of art itself.History of Art and Architectur
The Jewish Beat: Klezmer, Culture, and Community in Postwar America
No full textThis dissertation recovers the history of American Jewish wedding music during the early postwar period (1945–1965), shedding new light on the interplay between musical genres, social practices, and Jewish identity. In the wake of World War II and the founding of the State of Israel (1948), most American Jews drifted away from Yiddish language and culture. According to most scholarly accounts, klezmer, the traditional folk music of Yiddish-speaking Jews, virtually disappeared and was rarely performed before the so-called “klezmer revival” of the 1970s. I argue, however, that klezmer not only endured but formed the foundation for postwar American Jewish dance music. Although the traditional klezmer repertoire receded, its style blended with Israeli and American popular genres, leading to the creation of a new, hybrid form: the “klezmerized” Israeli folk song. My analysis thus reframes the relationship between Yiddish and Hebrew popular music, reading against the grain of their supposed opposition to reveal a complex, dialectical exchange between these two musical cultures that persists to this day.
This study demonstrates the central role of music in sustaining diaspora identities and communities. Even as many other Jewish rituals faded, Jewish dance music remained a staple at nearly all postwar Jewish weddings. Across social, cultural, and demographic lines, American Jews continued to view it as a vital expression of Jewish identity and a defining element of their celebrations. As I show, Jewish dance music was uniquely suited to this role thanks to its broad accessibility, aesthetic adaptability, and deeply embodied nature. Furthermore, I demonstrate that the discourse surrounding Jewish music, shaped by musicians, audiences, critics, and the recording industry, reinforced essentialist notions that rendered this music instantly recognizable to its listeners as distinctly “Jewish.” Thus, although the melodies changed, the style, performance practices, and social functions remained closely tied to klezmer traditions, reflecting a partial yet meaningful continuity with Ashkenazi heritage.
This study further highlights the affordances of a combined historical and ethnographic approach in music research, particularly the use of oral history to explore the connections between music, identity, and memory. Drawing on scholarship from music studies, cultural history, sociology, literary studies, and Jewish studies, I employ a hybrid approach that integrates archival research, ethnography, and musical analysis. My findings are grounded in archival work in New York and Israel, sound recordings, and more than one hundred oral history interviews with postwar wedding musicians and individuals married during that period. Taken together, these sources challenge prevailing narratives about postwar Jewish music, revealing how political ideologies shape perceptions about music and how music, in turn, constructs collective memory.Musi
Inflammatory cytokines induce novel cancer dependencies
Get PDFTumor cells respond and adapt to environmental stresses such as cytokine-mediated inflammation, triggered by anti-tumor immunity and enhanced by immune checkpoint blockade. While these adaptations promote tumor survival, they also induce transcriptional, metabolic and cellular state changes that create exploitable vulnerabilities. To map these inflammation-induced synthetic lethalities, we performed in vitro genome-scale CRISPR loss-of-function screens across eight murine and eight human cancer models exposed to IFNγ, IFNβ, or TNFα. Our study revealed that cytokine dependencies in cancers align with evolutionarily conserved pathways, including antiviral signaling, autophagy, vacuolar protein sorting, and peroxisome biogenesis. Unexpectedly, we identified novel roles for the ER enzymes glycosylphosphatidylinositol (GPI) transamidase and lipid phosphatase FITM2 in restricting interferon-driven stress responses. Loss of these enzymes in tumors triggered innate sensitivity to interferons in vitro , and enhanced responses to immune checkpoint blockade in vivo . Using genome-interaction screens, metabolomics and pharmacological inhibitors, we uncovered the molecular mechanisms by which the GPI transamidase and FITM2 sensitized tumors to IFNs. Specifically, tumors lacking GPI transamidase activity initiated an antiviral response mediated by the molecule tetherin, leading to cell death. Similarly, FITM2 loss disrupted lipid homeostasis, sensitizing tumor cells to innate intracellular defense molecules known as interferon-inducible GTPases. These GTPases orchestrated a series of cellular stresses — ER stress, oxidative stress, and autophagy — culminating in a distinct form of cell death termed paraptosis. Our findings thus provide a broad resource of tumor-intrinsic adaptations to inflammation, which can be exploited to overcome immune evasion or directly eliminate tumors.Immunolog
Laser Cooling, Optical Trapping, and Quantum Control of Polyatomic Molecules
Get PDFPolyatomic molecules contain diverse structures – including rotational and vibrational degrees of freedom, nuclear and electronic spins, and electric dipole moments – that make them promising for a range of quantum science applications. These include quantum information science, quantum simulation, studies of ultracold collisions and ultracold chemistry, and precision searches for physics beyond the Standard Model. However, maximizing the potential of polyatomic molecules for these applications requires them to be cooled to ultracold temperatures ( mK), trapped in three dimensions, and controlled at the single quantum state level. Significant progress has been made with diatomic molecules over the last fifteen years, but the increased complexity of polyatomic species (defined as molecules containing more than two atoms) makes them more challenging to control at the same level.
In this thesis, we describe our work bringing a linear triatomic molecule, calcium monohydroxide (CaOH), into the quantum regime. We demonstrate laser cooling of CaOH molecules to microkelvin temperatures, confinement in a magneto-optical trap (MOT), and loading of conservative optical dipole traps and optical tweezer arrays. We characterize the lifetime of low-lying vibrational states of CaOH in optical traps, including the vibrational bending mode, whose parity-doublet states are a key resource for many applications. Next, we develop techniques for preparing CaOH molecules in a single internal quantum state and for coherently manipulating the internal state with microwave and radio-frequency fields. We also show that we can nondestructively and state-selectively detect trapped CaOH molecules, including single molecules in optical tweezers.
We demonstrate the applicability of these tools to applications including precision measurements, quantum information science, and ultracold collisions. We establish a method for future CP-violating physics searches with optically trapped polyatomic molecules, by identifying states that are sensitive to the electron electric dipole moment (eEDM) and showing that these states have long coherence times in CaOH. We identify potential qubit states in the CaOH bending mode and show that they can be coherently controlled at the single-molecule level in an optical tweezer array. Finally, we observe and characterize single quantum-state-controlled collisions between ultracold CaOH molecules, and identify states in the bending mode that could potentially be used for evaporative cooling to quantum degeneracy.
Compared to linear triatomic molecules, nonlinear molecules contain even more structures that can be harnessed for quantum science applications, at the cost of making them even more challenging to cool and control. Towards this goal, in this thesis we describe work demonstrating 1D laser cooling of a beam of CaOCH3, a symmetric top molecule. This contributes to a growing body of evidence that complex polyatomic molecules could soon be cooled, trapped, and controlled at ultracold temperatures.Physic
Visualization of Entangled Hydrogel Granules for Injectable Gel Therapies
Get PDFInjectable hydrogels show promise for minimally invasive medical treatments, but current granular hydrogels often disintegrate post-injection, limiting their clinical effectiveness. Novel entangled U-shaped granule hydrogels have been developed to address this challenge, potentially enhancing applications in cell behavior modulation, drug delivery, and non-invasive surgery. However, to optimize these gels for specific medical uses, a method to visualize and quantify their 3D microstructure is needed. This project aims to develop a software tool that produces 3D reconstructions of these hydrogels and quantifies key characteristics such as void fraction, pore size distribution, and number of entanglements.Engineering Sciences S
Identifying Predictors of Success in Youth Mental Health Care: A Random Forest Analysis of Evidence-Based Treatment in Outpatient Community Clinics
Get PDFObjective: Research has shown dozens of treatment protocols to be effective in addressing mental health problems in youth. However, the research has focused largely on group-level effects, with less research examining which youths respond to a given treatment option. The research that has tested predictors and candidate moderators of treatment effects has largely relied on regression analyses. Recently, psychological treatment research has begun to incorporate various machine learning (ML) techniques, and these methods are presumed to outperform regression analyses; however, few studies have tested this assumption. This dissertation included two studies designed to help fill that gap. Both studies aimed to identify predictors of youth psychotherapy outcomes using traditional regression methods and using ML—random forest, specifically—so that findings with the two methods could be compared. Study 1 used data from youths who were treated with Trauma-Focused Cognitive-Behavioral Therapy (TF-CBT). Study 2 used data from youths who were treated with the Modular Approach to Therapy for Children (MATCH). Both studies addressed three questions: (1) Do youth characteristics predict treatment outcomes with random forest? (2) Do clinician factors predict treatment outcome with random forest? and (3) Does random forest outperform traditional regression in the prediction of treatment outcomes from youth characteristics and clinician factors?
Method: Participants were youths ages 7-19 who were treated with TF-CBT (N1 = 5503) or MATCH (N2 = 2292) in outpatient clinics in Connecticut between 2012 and 2022. For each treatment, a random forest and regression model were built to predict symptom outcomes using youth demographics (e.g., age at intake), youth clinical features (e.g., baseline symptom severity), clinician demographics (e.g., sex), and clinician professional features (e.g., licensure status). An additional regression model was built to predict symptom outcome using only the baseline severity on the outcome measure to assess whether the additional predictors included in the other two models enhanced predictive accuracy. Variable importance data and a feature selection program, both based in random forest, were used to identify important predictors for answering questions (1) and (2). Root mean squared error and R2 were calculated on a withheld test set to compare model fits for question (3).
Results: In study 1, TF-CBT outcomes on the Child PTSD Symptom Scale (CPSS) were predicted by 10 youth features and 4 clinician features. The baseline score on the CPSS was the strongest youth-based predictor, with higher baseline symptoms associated with larger improvement but ultimately higher symptoms after treatment; TF-CBT credential status was the strongest clinician-based predictor, with youths seeing credentialed clinicians demonstrating a poorer symptom outcome compared to those seeing uncredentialed clinicians. The random forest generated a stronger predictive model for the test set than either regression approach (R2 = 0.61, RMSE = 6.48). In study 2, MATCH outcomes on the youth reported Ohio Problem Severity Scale were predicted by 12 youth features and 5 clinician features. The baseline report on the outcome measure was the strongest youth-based predictor of outcome, again with more symptomatic youth at baseline showing larger improvements but ultimately remaining more symptomatic after treatment. Hours of MATCH training completed was the strongest clinician-based predictor of outcome, with youth symptoms declining as clinician MATCH training increased to 70 hours. The random forest generated a stronger predictive model than either regression approach (R2 = 0.45, RMSE = 6.30).
Conclusions: In both studies, random forest outperformed traditional regression analyses, but the margin of benefit varied. Psychologists and other statisticians should consider the purpose of their analyses (namely, predictive accuracy versus feature identification versus effect quantification) when selecting between random forest or other machine learning methods and regression, since the “black box” nature of machine learning means its accuracy comes at the expense of model interpretability. Youth clinical features, especially baseline symptom severity, explained much of the outcome variance. Modular, transdiagnostic treatments may be more challenging than more standardized treatments to model accurately because of the individualized course of treatment for each youth. To explain the variance that remains unaccounted for across the two studies, future work may benefit from the inclusion of features that were not measured here, including clinician “soft skills” like warmth and youth features like treatment motivation, as well as the investigation of appropriate outcome measures for analyses of transdiagnostic treatment protocols (i.e., different measures for different presenting problems).Psycholog