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Exploiting Genomic Instability to Improve Immunogenicity of Colorectal Cancer
No full textThe vast majority of colorectal cancer patients (~85%) present with tumors that exhibit minimal
immune cell infiltration and are consequently unresponsive to immunotherapy1. Therefore, it is
crucial to develop strategies that enable these patients to benefit from immunotherapy by priming
the immune system to recognize and attack cold tumors. We propose a strategy to induce tumor
cell genomic instability to make immunologically unresponsive tumors sensitive to immune
control. Tumor genomic instability leads to the mislocalization of nuclear chromosomal DNA
into micronuclei that are extruded into the cytoplasm. Upon rupture of the fragile micronuclear
envelope, the released chromosomal fragments activate innate immune nucleic acid sensors and
trigger downstream inflammatory pathways that cause immunogenic cell death. In our studies,
treatment with mitotic spindle checkpoint protein MPS1 inhibitor, BAY-1217389, did not
enhance antitumor efficacy, due to the low basal expression of inflammation-related genes in
tumor cells. However, by combining the MPS1 inhibitor with decitabine, a clinically approved
DNA methyltransferase inhibitor that derepresses the expression of innate immune genes in
murine models of colorectal cancer, tumor growth was controlled without systemic toxicity and
the antitumor immune response to immunotherapy was enhanced. Our findings suggest that
augmenting tumor genomic instability, coupled with a DNA hypomethylating drug decitabine,
could improve colorectal cancer responsiveness to immunotherapy.Graduate Educatio
Algorithms of arousal: an investigation of Pornhub videos and advertisements recommended to browser sessions without prior viewing
No full textThis paper explores the characteristics of videos and advertisements recommended to browser sessions without prior viewing on Pornhub, focusing on the relationship between aggression and the race of female performers. To do so, it relies on a manual review of ads and on data obtained through the use of scripted browser instances visiting porn sites to model what recommendations are present in actual visiting users’ experience. The specific question it aims to answer is how the level and kind of aggression varies based on the female performer’s race/ethnicity in videos recommended to fresh browser sessions. The paper is inspired by recent writings by Adler (2024) and Srinivasan (2021) that draw attention to the harms the way porn today is consumed causes. Both discuss the view that sexual tastes are not self-determined and biologically essential but influenced by porn. As such, porn’s harm is conceptualized both in the direct and horrible toll its production can take but also in the way pornography that is widely consumed influences sexual norms, and as they are closely intertwined with sexuality, gender norms. The paper’s main findings are that in 2025, on Pornhub the ads shown to browser profiles without prior interaction are exclusively sexuality related, targeted towards men and mainly feature white women. For the videos recommended, based on the tags and categories found on the site, the ones that feature female performers of color also have aggressive terms more often. The effect is more pronounced for search results, but overall presence of aggressive tags or categories are higher for homepage recommendations. This finding is broadly in line with previous literature, most notably Shor and Golriz’s 2019 article Gender, Race, and Aggression in Mainstream Pornography, an important inspiration, with this paper having a significantly larger sample size but relying on external categorization for its operationalization of key categories.Computer Scienc
Essays in Behavioral Development Economics: Social Frictions in Labor and Learning
No full textThis dissertation presents three essays in behavioral development economics that study how social and psychological frictions shape the effectiveness of development policies and programs. While large-scale investments in development have contributed to substantial reductions in global poverty, interventions can generate muted or heterogeneous impacts.
The essays examine how emotions, social norms, stigma, and interpersonal relationships influence behavioral responses to policies aimed at improving well-being, productivity, and aid allocation.
The first chapter studies the role of peer group structure in shaping the effectiveness of a school-based trauma intervention in Zimbabwe. Using a randomized controlled trial across lower-secondary schools, I evaluate a program that combines teacher training with a student-facing, peer-based intervention known as Freedom Clubs. I develop a simple model in which participation in group-based trauma programming entails social image costs that vary with relational closeness. Consistent with this framework, I find that treatment effects on trauma-related outcomes are heterogeneous: impacts are strongest when students are grouped with either very close peers or relative strangers, and weakest at moderate levels of closeness. Given the limited number of schools and clusters, statistical power is constrained and the resulting estimates should be interpreted cautiously. Noticeably, average effects are small and imprecisely estimated. Teacher training alone also yields few consistent benefits, with point estimates that, while imprecisely estimated, tend to move in negative directions.
The second chapter examines how inequality generates behavioral responses in low-income labor markets and how informal redistributive institutions may mitigate these responses. Using original survey data from rural western Kenya, I document strongly egalitarian fairness preferences, widespread expectations of envy and sanctioning following unequal gains, and the ubiquity of social and kinship taxation. Experimentally varied hypothetical scenarios show that inequality is expected to substantially increase harmful sanctioning behaviors, but that these effects are attenuated when advantaged individuals are embedded in resource-sharing relationships, particularly when inequality arises through luck rather than favoritism. The chapter also presents a pre-analysis plan for a lab-in-the-field experiment with sugarcane factory workers to test these mechanisms under real incentives.
The third chapter studies the political economy of development assistance by examining how U.S. cargo preference regulations affect the allocation of food aid. Using historical data on U.S. food aid shipments and freight rates, I show that cargo preference requirements raise transportation costs and distort aid allocations.Public Polic
Molecular mechanisms underlying regulation within the ubiquitin proteasome pathway
No full textTight regulation of protein homeostasis is critical for maintaining cellular processes. The ubiquitin proteasome pathway (UPP), one of the core regulatory pathways within the cell, acts globally to orchestrates protein stability. Ubiquitin is a finely conserved, 76 amino acid protein, featuring a β-grasp fold with a six amino acid tail at its C-terminus. The covalent transfer of ubiquitin, a 76-amino acid (aa) post-translational modification, to a protein target is a tightly regulated process, enacted through a three-part cascade. First, ubiquitin activation by the E1 enzyme (n = 2, humans) results in ubiquitin thioester bond to a ubiquitin-conjugating E2 enzyme (n > 50, humans) in an ATP-dependent fashion. Following, the formation of ubiquitin-protein conjugates is catalyzed by E3 ubiquitin ligases (n > 600, humans). Substrate specificity of ubiquitin transfer is regulated by the diversity of E3 ubiquitin ligases, whereas specificity of ubiquitin transfer is regulated jointly by the E2 and E3 enzymes. Collectively, the ubiquitin proteasome pathway forms a reversible, interconnected quality control network self-organized through biophysical properties and subcellular compartmentalization.
A fundamental question is how substrate is selectively targeted for proteolysis. In part one of this thesis, through structural and biochemical techniques, we explore how a prototypical ubiquitin ligase uses a cryptic ubiquitin binding site to constrain activity and confer chain selectivity within its distal catalytic domain. We leverage cryogenic electron microscopy to determine an atomic model of the apo-ligase and low energy intermediates associate with ubiquitin transfer. We demonstrate that the ligase architecture and domain motions of the noncatalytic modules is finely conserved between S. cerevisiae ortholog Tom1 and human ortholog HUWE1. Our model sheds light on how patient mutations distal to the catalytic module could influence activity of the human HUWE1.Biological and Biomedical Science
How Feedback Shapes Galaxies and the Stories We Tell About Science
No full textGalaxies evolve through a continuous exchange of mass and energy with their surroundings, a process known as the baryon cycle. ``Feedback" from stars and supermassive black holes, in the form of radiation and winds, is predicted to regulate this cycle by modulating how gas cools, forms stars, and is reheated and/or expelled. This dissertation explores how feedback operates across a range of environments and mass scales, using a combination of multi-wavelength observations and theoretical modeling.
The first two chapters examine the impact of supermassive black hole / active galactic nuclei (AGN) feedback in the Universe's most massive galaxies through multi-wavelength observational studies of the SDSS J1531+3414 () and Abell 2597 () clusters of galaxies. In SDSS J1531+3414, I identify one of the most powerful AGN outbursts known, releasing over of energy. This outburst is traced by a giant X-ray cavity and steep-spectrum fossil radio lobes, with a reservoir of of molecular gas tangentially connected to it. The gas appears to have been uplifted by the powerful outburst, and is now spatially offset from a striking 28 kpc-long chain of 19 stellar superclusters. Together, these features suggest that a recent major merger has disrupted the feedback loop in the cluster's central massive galaxy, decoupling star formation from the cold gas that fuels it.
In contrast, Abell 2597 hosts a more stable, long-lived feedback loop. Deep \textit{Chandra} X-ray observations reveal multiple generations of AGN feedback-driven cavities and potential 150 kpc-scale shocks, consistent with recurrent AGN outbursts on 10 year timescales. Although the AGN injects mechanical energy at a rate of erg s, sufficient to prevent overcooling, infrared and millimeter observations reveal that residual cooling persists at 15 \msun\ yr, maintaining a \msun\ cold gas reservoir draped around the cavities in the central galaxy. These features point to ongoing condensation from the intracluster medium, likely aided by AGN-driven uplift, and suggest that cold gas accretion—not hot-mode Bondi flow—sustains the central AGN.
To extend this analysis beyond the massive galaxies at the centers of clusters and into the lower-mass regime where stellar feedback dominates, Chapter 3 introduces the TNG SAM, a new semi-analytic model of galaxy formation. Built on the Santa Cruz SAM framework and calibrated to baryon flows measured in the IllustrisTNG-100 simulation, the TNG SAM captures key physical processes shaping galaxies in halos from to . Several major updates distinguish the model: a cooling time-based prescription for gas accretion that replaces the classic hot/cold mode dichotomy; revised treatments of halo gas re-accretion and cooling; explicit modeling of both galaxy- and halo-scale outflows; and metallicity-dependent mass loading and metal enrichment prescriptions that track the circulation of gas and metals between galaxies and their environments. These changes allow the TNG SAM to reproduce IllustrisTNG predictions for stellar mass, cold and hot gas mass fractions, and gas and stellar metallicities to within , out to . As a result, the model offers a powerful, computationally efficient tool for interpreting the baryon cycle in galaxies where direct observations of the CGM remain limited.
Finally, this dissertation turns from the physical processes shaping feedback to the infrastructures, labor systems, and politics that shape the production of astronomical knowledge. Drawing on archival and historical records, I examine the role of Black South African workers in building and maintaining early 20th-century American observatories in South Africa. These workers, whose contributions have been largely excluded from the scientific narrative, laid the physical foundations that enabled U.S. institutions to extend their scientific reach into the Southern Hemisphere. By recovering these histories, I trace how systems of racial capitalism and settler colonialism materially structured the development of modern astrophysics—not only through the land and labor they extracted, but also through the epistemologies they reinforced. Just as feedback governs the cycling of matter and energy in galaxies, it offers a lens for understanding how knowledge itself is generated, sustained, and challenged within scientific institutions.Astronom
Structural and biophysical investigations of [4Fe-4S] cluster coordinating proteins in malaria and herbicide biosynthesis
No full textRadical S-adenosylmethionine (RS) enzymes are the largest known enzyme superfamily, consisting of millions of reported sequences. RS enzymes use a [4Fe-4S] cluster to reductively cleave a S-adenosylmethionine (AdoMet) molecule to form a 5′-deoxyadenosine radical (5′-dAdo•). By using the 5′-dAdo•, RS enzymes catalyze a diverse portfolio of chemically difficult reactions. Cobalamin (Cbl)-dependent RS enzymes comprise a subfamily within the RS superfamily which employ both Cbl and 5′-dAdo• to catalyze reactions. Recently, two enzymes were identified as essential for the production of the herbicidal compound Albucidin: the RS enzyme AlsA and the Cbl-dependent RS enzyme AlsB. In this dissertation, we present our progress toward an X-ray crystallographic structure of AlsA and a cryogenic-electron microscopy (Cryo-EM) reconstruction of AlsB. The X-ray diffraction of AlsA crystals is low resolution, mosaic, and twinned, resulting in a 3.7 Å resolution electron density map with a disordered active site. Using Cryo-EM, a 7.12 Å resolution map of AlsB was generated. At 83.5 kDa in size, AlsB is small for Cryo-EM. The Cryo-EM map of AlsB closely resembles a closed conformation of the enzyme, a conformation that remains unobserved in the similar Cbl-dependent RS enzyme OxsB. Additionally, we describe an optimized procedure for the chemical reconstitution of AlsA suitable for structural studies. To assess the thermal stability of AlsA, a NanoDSF-based thermal shift assay was developed, demonstrating the presence of two protein populations. The two populations, hypothesized to be reconstituted and unreconstituted AlsA, react differently to the presence of dithiothreitol, a commonly used reductant for RS enzymes. Our findings suggest thermal shift assays can visualize heterogeneity in protein samples that otherwise could not be observed. Also, NanoDSF provides us with a high throughput method for determining suitable buffer conditions for structural studies for RS enzymes and other oxygen sensitive proteins. Finally, we report the second X-ray crystal structure of the essential lipocalin HAL from the malaria-causing parasite Plasmodium falciparum. Our crystal structure solved in the C2 space group shows a crystal lattice formed by repeated dodecamer rings. We identify chloride anion sites between two monomers, suggesting a role for chloride in the oligomerization of PfHAL. Altogether, this work provides a foundation for the structural investigation of Albucidin Biosynthesis and provides new information toward understand of the role of PfHAL in malaria.Biophysic
Cathodoluminescent Probes for Multicolor Electron Microscopy
No full textCathodoluminescence (CL) microscopy offers a promising approach to nanoscale analysis, enabling detection of optical emission from a sample while leveraging the high resolution of electron microscopy (EM). However, achieving multicolor single-particle CL imaging remains a significant challenge. Here, we establish lanthanide nanoparticles (LNPs) as a model system for multicolor CL imaging. We identify the critical limitation that precluded multicolor CL imaging—nonlocal signal caused by stray electrons—and mitigate these nonlocal excitations to demonstrate multicolor single-particle CL imaging.
To be viable for multicolor CL imaging applications, LNPs must be available in multiple emission colors. Therefore, having achieved single-particle CL imaging, we use this method to study the photophysical properties of LNPs and expand their multiplexing capability. We determine the dependence of LNP brightness on lanthanide ion concentration, develop a method to measure CL excited state lifetimes of LNPs, and study energy transfer between lanthanide ions. Next, we combine multiple lanthanide elements to engineer unique LNP colors and use them for seven-color CL imaging.
Applying CL probes as bioimaging labels would enable simultaneous visualization of cellular structures (via EM contrast) and specific biomolecules (via CL contrast) at the nanoscale resolution of EM. However, achieving this is challenging because LNP synthesis yields hydrophobic nanoparticles, limiting their utility as bioimaging labels. To address this challenge, we functionalize LNPs with DNA to produce hydrophilic LNPs. We show that their single-particle CL emission is retained after DNA functionalization and after common EM sample preparation steps, and demonstrate nanoscale, multicolor CL imaging of DNA-functionalized LNPs in a biological sample.
Finally, we explore the viability of small-molecule fluorescent dyes as CL labels. We show that these dyes can be excited by an electron beam and emit CL signal. We demonstrate three-color CL imaging using dye-loaded polymer beads, and two-color CL imaging of mammalian cells with dye-labeled organelles, illustrating the potential of small-molecule fluorescent dyes for CL bioimaging. Together, this work establishes CL as a useful contrast mechanism for high-resolution, multicolor electron microscopy and represents a significant step toward the application of cathodoluminescent probes for simultaneous imaging of cellular structures and biomolecules.Biology, Molecular and Cellula
Multiplexed auditory synchronization: Measuring distraction in listeners with normal hearing and with tinnitus
No full textDespite numerous sounds presented to our ears, people typically want to choose to listen to only one. Some unwanted sounds can be distracting and harder to suppress while others are just background noise. Along with environmental sources of sound, individuals with tinnitus have an additional competitor: an unflagging auditory percept with no external generator. For some individuals with tinnitus, this phantom sound impinges on them constantly; for others, the phantom fades harmlessly into the background unless they attend to it. The difference in how these groups experience tinnitus may be related to their abilities to suppress distracting sounds more generally.
To test this hypothesis, we developed a novel paradigm for measuring behavioral and neurophysiological measures sensitive to the level of distraction provided by competing sounds. Participants are presented with a target stimulus organized around nested timescales, including temporal fine structure (~500 Hz), envelope (~25-80 Hz), envelope changes (~7 Hz), and embedded context (~0.5 Hz). EEG is recorded to capture synchronization to the features across these timescales as participants make perceptual judgments about the embedded context. These target stimuli are presented alongside two different types of distractors—melodic and noise distractors—which share low-level acoustic features but differ in the amount of distraction they produce.
Normal hearing participants are more distracted by the melodic distractors than the noise distractors. While the inclusion of the distractor reduces synchronization across all timescales, only the slowest synchronization to envelope changes, the envelope change following response (ECFR), is sensitive to the level of distraction. The ECFR is reduced when the target is paired with the melodic distractor compared to the noise distractor and is also reduced when participants make errors in perceptual judgment about the target stimulus. Results in participants with tinnitus are in line with results from participants with normal hearing. When behavioral and ECFR results are compared between a group with lower tinnitus burden and a group with greater tinnitus burden, the groups do not differ.
Our novel paradigm simultaneously provides information about synchronization to up to 9 different features of auditory stimuli at nested timescales. This paradigm has yielded the ECFR, a newly described synchronization measure that is sensitive to the level of auditory distraction. Such a measure may prove useful in a variety of populations who have difficulty suppressing awareness of unwanted sounds. In participants with tinnitus, this measure was not associated with the level of tinnitus burden, suggesting that suppression of externally presented distractors and internally generated phantom sounds utilize different resources.Speech and Hearing Bioscience and Technolog
Robust Causal Inference Methods for Electronic Health Record-Based Studies with Missing Eligibility and Calendar Time-Varying Treatment Effects
No full textElectronic health records (EHR) are seen as useful alternatives to randomized controlled trials when the latter are infeasible due to financial, ethical, or logistical constraints. Unfortunately, EHR exist to record clinical activity and assist with billing, and thus information is not collected with research in mind. When using EHR to study comparative effectiveness, there are many factors that a researcher can not control: treatments are not randomly assigned, information on certain patient covariates may be unavailable, when to begin follow-up is not always clear, and which patients receive treatment and why may change over time. As such, rigorous statistical methods which contend with these factors, often simultaneously, are necessary when conducting EHR-based studies.
In Chapter 1, we consider the problem of selection bias due to missingness in covariates which define study eligibility in target trial emulations. We illustrate the dangers of naively excluding patients missing certain eligibility-defining covariates and propose a solution based on a novel missing at random assumption using inverse probability weighting. Our solution integrates seamlessly within a larger framework for dealing with common sources of bias in sequential target trial emulations, such as confounding, non-adherence, and censoring.
Next, in Chapter 2, we extend the ideas of Chapter 1 and propose a robust and efficient estimator of the causal average treatment effect on the treated, defined in the study eligible population, in cohort studies where eligibility-defining covariates are missing at random. The approach facilitates the use of flexible machine-learning strategies for component nuisance functions while maintaining appropriate convergence rates for valid asymptotic inference, and displays robustness to various degrees of model misspecification in the component nuisance functions.
Finally, in Chapter 3, we formalize sequential target trial emulations for continuous outcomes and propose a statistical framework to describe both how and why causal effects vary over treatment initiation time in EHR-based studies. Our approach projects doubly robust, time-specific treatment effect estimates onto candidate marginal structural models and uses a principled model selection procedure to best describe how effects vary by treatment initiation time. We further introduce a novel summary metric, based on standardization analysis, to quantify the role of covariate shift in explaining observed effect changes and disentangle changes in treatment effects from changes in the patient population receiving treatment.
The statistical methods developed in this dissertation are motivated by real EHR-based studies of bariatric surgery at Kaiser Permanente. Throughout, we use these data to both illustrate and validate the methods introduced in this work.Biostatistic
Swing and a Miss: Uncovering Behavioral Biases in MLB Betting Markets
No full textSports betting is a rapidly growing industry, gaining attention from sports fans, professional investors, and academia. Its attractiveness not only lies in the excitement about sports and potential rewards from betting itself, but also because it serves as a ground to study risk-taking and irrationality. This thesis investigates two of the most widely discussed biases, the favorite–longshot bias and momentum, within the MLB betting market. Using moneyline and run-line odds, as well as the evolution from opening to closing lines, we analyze whether these behavioral patterns persist in pricing and whether they offer exploitable trading opportunities. Our findings show that the favorite–longshot bias is clearly present in opening odds but disappears in closing odds, with stronger effects observed in home games. Momentum affects how teams are assigned to favorite or underdog categories, yet the market efficiently prices streak-related information. Similar patterns emerge in run-line markets. Although certain momentum-based signals appear promising for systematic betting, their economic value is too small to overcome transaction costs such as the bookmaker’s vig. Overall, this thesis provides a variety of evidence that the favorite-longshot and momentum bias are present in baseball betting markets, and that they stem from biases in bettor behaviors.Applied Mathematic