Studies in Algebraic Cycles: Hodge Theory of Degenerations, Regulators, and Cluster Varieties

This dissertation brings together results in Hodge theory and the theory of cluster varieties. The second chapter, based on a paper written in collaboration with Devin Akman and Matt Kerr, uses admissible normal functions to establish the first finiteness result for zero-dimensional components of the Hodge locus. The third chapter, based on joint work with Matt Kerr, shows that weak polar- ized relations constrain possible adjacencies of mixed Hodge structures across boundary strata in geometric compactifications. The fourth chapter gives a geometric construction of a 6-dimensional cluster variety with a disconnected mutation graph, as discovered by Yan Zhou. These three chap- ters employ different techniques, but they are tied together by the common threads of algebraic cycles and the Hodge theory of degenerations

Advancing Precision Treatment of Multiple Myeloma with Single-Cell and Spatial Immune Profiling

Multiple myeloma (MM) is a highly refractory hematologic malignancy for which targeted immunotherapy and stem cell transplant have shown great promise. Two key challenges in advancing treatment lie in identifying broadly representative tumor markers and understanding the how post-transplant bone marrow (BM) immune repopulation influences treatment outcomes. Recent technological developments in single-cell RNA-sequencing (RNA-seq) and probe-based spatial transcriptomic assays now allow us to perform deep molecular characterization, interrogating cellular heterogeneity and interaction at unprecedented granularity. My dissertation leverages these platforms to uncover therapeutic targets and enhance our understanding of transplant-induced bone marrow remodeling. First, I utilize scRNA-seq to analyze BM aspirates from MM patients, applying a high-throughput, unbiased pipeline to identify candidate MM marker genes, including novel markers not yet under clinical investigation and previously characterized as potential therapeutic targets. These findings were cross-validated using bulk RNA sequencing, flow cytometry, and proteomic mass spectrometry, confirming the ability of single-cell technologies to accurately capture marker expression despite sample size and sequencing depth limitations. Next, I focus on understanding how BM dysregulation impacts MM treatment outcomes, particularly after autologous stem cell transplantation (ASCT). We conducted scRNA-seq on post-transplant BM aspirates, alongside samples from newly diagnosed MM patients and healthy controls, revealing immune features linked to MM pathogenesis and transplant response. These included dysregulated NFκB signaling in MM plasma cells and naive B cells, increased T cell exhaustion, and altered myeloid signatures associated with tumor burden and survival outcomes. Using probe-based spatial transcriptomics, we further mapped the BM microenvironment, observing compartmentalization of lymphocyte- and progenitor-rich regions and disruption of early B cell developmental niches, which correlated with treatment outcomes. This study underscores the importance of the BM milieu in post-transplant responses and provides new insights into how spatial and immune dysregulation contribute to treatment resistance in MM. Together, these findings demonstrate the power of single-cell and spatial transcriptomics in uncovering new therapeutic targets and elucidating the complex BM microenvironment in MM, offering promising avenues for enhancing precision medicine in MM treatment

Exploring the Thermal Physiology Evolution Across Mountain Slopes

I investigated whether critical thermal limits to low and high temperatures exhibit patterns of thermal tolerance specialization across altitudes, both between and within species, in the complex terrain of the Neotropical mountains. In these mountains, species have found different ways to adapt and diversify to their various elevational and climatic gradients (Chapter 2). I used climatic and distribution data to assess patterns and test for changes in the evolution rates of highland specialization across the entire anole phylogeny. Few animal groups have been able to adapt and thrive in several different mountain ranges (Chapter 3). I tested whether those biogeographical shifts from low elevation to high elevation have led to an increase in diversification and speciation rates (Chapter 4). Finally, I tested whether water loss is influenced more by the intrinsic physiology of the lizards or by the climatic niche they inhabit. I also investigated to what extent these two factors affect water loss in lizards (Chapter 5). I found that understanding the evolution of highland specialization and climatic niche evolution is particularly complex. Different clades have converged in their critical thermal limits, where the critical thermal minimum and maximum decrease as elevation increases (Chapter 2). This convergence suggests that high-elevation environments exert strong selective pressures that shape the thermal tolerances of species. Additionally, cold adaptation has evolved several times in similar ways when analyzed within an elevational and cold temperature framework (Chapter 3). This repeated pattern of adaptation highlights the predictability of evolutionary responses to similar environmental challenges. However, I observed distinct evolutionary trajectories between highland and lowland species, likely shaped by climatic heterogeneity and ecological specialization across elevation gradients (Chapter 4). Factors such as the temporal scale of analysis, the specific environmental variables considered, the phylogenetic context, and the climatic heterogeneity all play crucial roles in shaping our understanding of climatic niche evolution. Lastly, I discovered that water loss is intricately associated with climatic conditions, particularly temperature and precipitation (Chapter 5). The relationship between water loss and climate suggests that species have evolved mechanisms to cope with varying levels of humidity, precipitation and temperature. This adaptation is critical for maintaining hydration and overall physiological function in desertic regions

Functional and Structural Connectivity as Predictors of Long-term Motor Development in Very Preterm Children with and without Brain Injury

Preterm birth is a major cause of lifelong motor disability that has significant impacts on multiple domains of quality of life, yet individual-level outcome prediction and understanding of specifically when and where the brain is impacted remains limited. This thesis examines neonatal functional (FC) and structural (SC) connectivity as potential predictors of motor outcomes through age ten years in very preterm children with and without brain injury. Findings are presented with age two outcomes in Chapter 2, age five outcomes in Chapter 3, and age ten outcomes in Chapter 4. All three include FC. Only chapter 4 excludes the children with brain injury due to the different ages of subsets of the cohort, and only Chapter 4 includes SC. Overall, there are two patterns of brain measures and later impairment, differing by brain injury status. Among children with brain injury, cerebral palsy is common and identifiable by age two. FC between left and right motor cortex is correlated with motor scores at two and five years, but age ten was not tested. Among children without brain injury, most motor impairment is not apparent at age two but is by age five and persists at age ten, appearing in alignment with a developmental coordination disorder pattern. Cerebellum-motor cortex FC is predictive of balance scores at ages five and ten years, while basal ganglia-motor cortex FC is related to age five fine motor scores. Fractional anisotropy of the left internal capsule is also related to fine and gross motor scores in this population. These two patterns of brain findings and later motor development may reflect the impacts of brain injury and abnormal early sensorimotor experiences respectively and may not be mutually exclusive. Neonatal FC and SC have potential for earlier identification of motor disability in very preterm children, which may enable earlier intervention, accommodation, family support, and integration into the disability community. Longer follow-up in this population is key to providing the necessary support to live happy, healthy lives

Parsing Heterogeneity in Depression

Depression is a highly prevalent mental health disorder that often requires treatment. While current treatments are effective for a large portion of patients generally, the exact medication that works for any specific person is unclear, leading to large delays in symptom remittance if at all. This hurdle has motivated substantial efforts to identify markers of depression that might predict treatment outcomes. However, large sources of heterogeneity in depression have stymied progress on identifying robust and replicable neuroimaging markers. Parsing this heterogeneity is crucial but mired with challenges. My dissertation work has elucidated several key barriers in parsing the heterogeneity of depression. In chapter 2, we identified small but replicable biomarkers of depression in the UK Biobank. In chapter 3, we found these small effect sizes for biomarkers of depression can be increased by parsing clinical sources of heterogeneity. We also verified the presence of many-to-one mapping relationships between symptoms and the brain, providing novel insights into the mechanism of depression. This finding strongly indicates future work ought to relinquish the notion that clinical subtypes will explain neurobiological heterogeneity and vice versa. Both symptoms and neuroimaging must be accounted for when identifying subtypes or clinically relevant markers of depression. In chapter 3, we identified the impact of methodological variability on subtyping efforts, identifying subtyping techniques to avoid and validation analyses to include. For example, we recommend future work compare their findings to null data and to previous subtyping approaches. These advancements will hopefully allow the field to successfully identify and parse the sources of heterogeneity in depression. Such progress should allow for more robust biomarkers of depression and therefore treatment guidelines, ultimately improving patient care

Digital and Physical Spaces: All at Once

In this thesis, I explore our experience of digital and physical spaces in the ever-increasing presence of technology. By investigating the intersections of these spaces, I focus on how our experiences in the physical world are processed through the digital space, to re-merge in lived spaces. Through digital collage paintings, I explore how assisted chance and machine destruction can be productive in the formation of space that is not possible on the screen. By using the drop shadow as primary content, my work takes on the arrangements of surface and space—rather than the requirements of the physical world. In addition, I use the physicality of paint to concretize the digital image into physical space and insert myself between both the digital and the physical world. Through my work, I hope to call attention to the way we process the digital space and physical space, all at once

Retirement Plan Access among Low-Wage Workers in 2024: Implications for SECURE 2.0

Households in the United States struggle to save for retirement, and the problem is acute for low- to moderate-income (LMI) households. In 2022, the federal SECURE 2.0 Act created an expansive suite of policy approaches to facilitate saving in LMI households. This brief discusses key provisions of the act and presents findings from the Workforce Economic Inclusion and Mobility (WEIM) survey of a nationally representative sample of vulnerable workers in the United States. The findings suggest opportunities to improve upon the SECURE 2.0 Act’s provisions

Quantifying Noise in Optical Redox Ratio Imaging

Characterizing cellular metabolism through noninvasive imaging of metabolic cofactors NAD(P)H and FAD has become a powerful diagnostic tool, with the Optical Redox Ratio (ORR) serving as a key quantitative metric. However, widespread adoption of ORR imaging is hindered by the lack of standardized image quality requirements. This study addresses that gap by analytically deriving expressions for the variance of ORR measurements as a function of photon shot noise and dark current contributions. Using statistical conditioning, we modeled the expected pixelwise ORR variance and verified the model through simulated image sets and experimental data. We observed that variance decreases with higher photon counts and frame averaging, aligning with theoretical predictions. The results showed strong correlation between analytical and empirical variance, even under varying noise conditions. This work provides a quantitative foundation for evaluating ORR image quality and can inform future acquisition protocols and data processing. Ongoing efforts include developing a MATLAB application for variance analysis and preparing a manuscript to disseminate these findings

Leveraging arginine catabolism to treat metabolic complications

Fasting and caloric restriction are effective to treat patients with pre-diabetes or metabolic dysfunction-associated steatotic liver disease (MASLD), previously known as non-alcoholic fatty liver disease (NAFLD), but intensive lifestyle changes are difficult for many to implement and sustain. Therefore, by identifying and studying fasting-mediated signals, we hope to elicit and convey the therapeutic effects of fasting against MASLD without actual physiological fasting. We discovered a key pathway in the liver through unbiased transcriptomic screening in fasted mice, a novel glucose fasting-activated effector: the amino acid hydrolase, arginase 2 (ARG2). Our previously published data demonstrates that forced hepatocyte-specific Arg2 overexpression is sufficient to reduce peripheral insulin resistance and hepatic steatosis in pre-diabetic and MASLD models in mice. In this thesis, I am to investigate how ARG2 conveys its therapeutic effects and examine its efficacy to bring forth new therapies that mimic the actions of ARG2 to ultimately treat MASLD and MASLD-related metabolic disease. In the first part of my thesis, I define the structure-function relationship between ARG2 mitochondrial localization, arginine hydrolase activity, and the metabolic effects of ARG2. I generated and tested two ARG2 mutant constructs, one lacking the putative N-terminal mitochondrial targeting sequence (MTS, Arg21-22) and the other lacking its ureahydrolytic activity (Arg2H160F). Hepatocyte-specific overexpression of the mutant constructs in obese, diabetic (db/db) mice showed ARG2 attenuates hepatic steatosis independent of mitochondrial localization or ureahydrolase activity, and that enzymatic activity is dispensable for ARG2 to augment total body energy expenditure. Furthermore, ARG2-mediated increase in glucose-, insulin tolerance, and glucose appearance suppression during hyperinsulinemic-euglycemic clamping requires both mitochondrial localization and ureahydrolase activity. Seahorse respirometry in hepatocytes in vitro, and quantification of heavy-isotope-labeled glucose oxidation in vivo further revealed that both Arg21-22 and Arg2H160F mutants failed to induce ARG2-mediated increase in hepatic and systemic oxidative metabolism, respectively. These results further complement our previous work in ARG2 by providing a structure-based mechanism of ARG2 with respect to its metabolic effects and demonstrating that hepatic Arg2 is a prominent metabolic gene. In the second part of my thesis, I investigate the contribution of and necessity for hepatocyte ARG2 in prevention against MASLD progression to confer the metabolic effects in the pathogenesis of MASLD and its related metabolic complications. The results demonstrate that hepatocyte-specific Arg2 deletion impairs ureagenesis, TCA cycle, and mitochondrial function which has real physiological metabolic consequences. Hepatocyte-specific Arg2-deficiency drives obesity, liver steatosis, and insulin resistance in aging-associated metabolic decline and diet-induced mouse models of MASLD. Mechanistically, impaired oxidative metabolism and MASH in Arg2LKO mice is reversible through supplementation of NAD+ via nicotinamide mononucleotide or nicotinamide riboside. Translationally, Arg2-deficiency generates metabolite alterations in nitrogen flux, TCA cycle flux, and oxidative metabolism which is consistent with biomarkers perturbation that independently predict severe incident MASLD/MASH nearly a decade in advance from 106,606 healthy participants in the UK Biobank. Therefore, hepatocyte-specific Arg2-deficiency represents as a new paradigm to demonstrate the urea cycle’s hierarchical control over TCA cycle flux to regulate mitochondrial oxidative metabolism. Together, providing mechanistic insight into the long-observed association between urea cycle impairment and MASLD. We then identified a readily available pharmacological reagent, ADI-PEG 20, and found arginine depletion via ADI-PEG 20 is viable and holds great therapeutic potential as a candidate for treatment against obesity and MASLD. Furthermore, ADI-PEG 20 treatment induced favorable metabolic effects that were independently abolished in mice with liver-specific Fgf21 and Becn1 deletion. This study reveals a novel role of arginine catabolism in the pathophysiology of MASLD which is dependent on liver-specific functions such as FGF21 and autophagy. Together, our findings suggest that hepatocyte arginine status is central and modifiable in treatments against MASLD and metabolic complications

The Conservative Case for Leaving Harvard Alone

The Supreme Court precedent allowing the IRS to revoke a university’s tax-exempt status is a textualist’s nightmare