DIGITAL ACCESS TO

Japanese architectural art history has traditionally characterized Nikkō Tōshōgū, the well-known mausoleum of the first Tokugawa shogun Ieyasu (1542-1616), as unique in terms of its overwhelming elaborate ornamental and architectural features. First built in 1617, and rebuilt by the third shogun Tokugawa Iemitsu (1604-1651) for his grandfather Ieyasu, it has primarily been framed as an example through which Iemitsu enhanced and legitimated his own political rule. What has been largely overseen is that architecturally Nikkō Tōshōgū in fact stands not alone, but instead triggered the development of an architectural typology of Edo period (1615-1868) religious architecture with similar aesthetics that began to spread all over the Japanese archipelago from the seventeenth century onward. During the Edo period (1603-1868) not only hundreds of smaller Tōshōgū were erected in the domains all over Japan to worship Tokugawa Ieyasu, the founder of the Tokugawa shogunate, but the numerous mausolea of the succeeding shoguns and their wives exhibited the same stylistic traits, were made by the same carpenter families, and served similar political and religious ends. Constructed with newly developed carpentry techniques under a new building system, the impact of the mausolea building typology in fact reached far beyond the confines of the Tokugawa familial mausolea and official Tokugawa government control. They influenced regional shrine and temple construction that was sponsored by the warlords in the domains, or financed on a local level by the townspeople. Despite the Tokugawa mausolea’s significance as representative elite architecture of early modern Japan, comparable to the imperial and royal tombs of China and Korea, and their role in transforming and systemizing the building culture as a whole in early modern Japan, currently they only occupy a marginal place of a few descriptive pages in our art history textbooks. In this dissertation, I explore this neglected sphere of early Edo period architecture, visual culture, and religion by focusing on Nikkō Tōshōgū and the mausolea of the successive Tokugawa shoguns and their wives. I trace their origins and attempt to propose new ways of understanding their architectural qualities, circumstances of construction, and political and religious context based on secondary, as well as primary sources. Through this examination, it is hoped to reframe their historical understanding and resituate them into their original context in Japan, and more broadly East Asia.

Current methods for detecting atmospheric plumes and inferring point-source rates from high-resolution satellite imagery are labor-intensive and not scalable with regard to the growing satellite dataset available for methane point sources. We present a two-step algorithm called U-Plume for automated detection and quantification of point sources from satellite imagery. The first step delivers plume detection and delineation (masking) with a U-Net machine learning architecture for image segmentation. The second step quantifies the point-source rate from the masked plume using wind speed information and either a convolutional neural network (CNN) or a physics-based integrated mass enhancement (IME) method. The algorithm can process 62 images (each measuring 128$\times$128 pixels) per second on a single 2.6~GHz Intel Core i7-9750H CPU. We train the algorithm using large-eddy simulations of methane plumes superimposed on noisy and variable methane background scenes from the GHGSat-C1 satellite instrument. We introduce the concept of point-source observability, $O_{\mathrm{ps}} = Q/(UW\Delta B)$, as a single dimensionless number to predict plume detectability and source rate quantification error from an instrument as a function of source rate $Q$, wind speed $U$, instrument pixel size $W$, and instrument-dependent background noise $\Delta B$. We show that $O_{\mathrm{ps}}$ can powerfully diagnose the ability of an imaging instrument to observe point sources of a certain magnitude under given conditions. U-Plume successfully detects and masks plumes from sources as small as 100~kg,h$^{-1}$ in GHGSat-C1 images over surfaces with low background noise and successfully handles larger point sources over surfaces with substantial background noise. We find that the IME method for source quantification is unbiased over the full range of source rates, while the CNN method is biased towards the mean of its training range. The total error in source rate quantification is dominated by wind speed at low wind speeds and by the masking algorithm at high wind speeds. A wind speed of 2--4~m,s$^{-1}$ is optimal for detection and quantification of point sources from satellite data (chapter 1).

The MethaneAIR aircraft remote sensing instrument observes methane dry air column mixing ratios (X$_{\mathrm{CH_4}}$) over $\sim$100$\times$100~km$^2$ scenes with sub-km resolution, from which methane emissions can be inferred by inverse analysis with an atmospheric transport model. It emulates the MethaneSAT satellite instrument that operated March 2024--June 2025 to quantify emissions from oil/gas production regions. We show here how the single-day MethaneAIR observations can be integrated with the global continuous but relatively coarse and sparse observations from the TROPOMI satellite instrument into a common Integrated Methane Inversion (IMI) platform for optimizing methane emissions. The IMI, originally designed for TROPOMI, is used here with 12$\times$12~km$^2$ spatial resolution and lognormal error probability density functions (PDFs) for prior estimates. Application to two scenes in oil/gas production basins of the western US shows general consistency between independent MethaneAIR (single day) and TROPOMI (monthly) inversions, including for emission hotspots, with some differences that may reflect temporal variability of emissions and/or unrecognized error correlations in the observations. The IMI is able to optimize emissions even when starting from a very poor prior estimate, although the prior estimate contributes information toward the optimized emissions. Using TROPOMI inversion results as prior estimate improves the MethaneAIR inversions by correcting emissions upwind of the MethaneAIR observation scenes and by adding information to the original prior estimate. (chapter 2).

The MethaneSAT satellite instrument, operating from March 2024 to June 2025, observed methane column concentrations over selected oil and gas basins with an unprecedented combination of sub-km spatial resolution and high precision. Here we conduct analytical Bayesian inversions of MethaneSAT observations with the Integrated Methane Inversion (IMI) to infer 13-month mean methane emissions at 25-km resolution and compare them to inversions of TROPOMI daily satellite observations over the same domain and period. We focus on the Permian basin, which MethaneSAT observed on 28 days, more than any other basin, and which has a high TROPOMI retrieval success rate (33% for the basin). The instruments have different vertical averaging kernel sensitivities, but we find that they are consistent in their observed column variability when using the GEOS-Chem forward model of the IMI as a common intercomparison platform. We find that IMI inversions of TROPOMI and MethaneSAT data agree in their basin and sub-basin totals but have large differences at fine resolution that could reflect variable point sources. MethaneSAT provides higher information than TROPOMI on its observation days but is limited by its return time and its small viewing scenes. The best inversion results are obtained when using the TROPOMI inversion results as prior estimates for the MethaneSAT inversion. Comparison to daily emission estimates from the MethaneSAT Level-4 product shows good agreement in the basin-scale magnitude of emissions, except for a subset of scenes where weak and/or variable winds complicate the treatment of large point sources. (chapter 3).

Tumor-infiltrating B cells (TIL-Bs) are emerging as important immune cells in immunotherapy response and clearance of tumors. However, the mechanisms and antigen specificities of TIL-Bs in the tumor microenvironment (TME) are not well understood. In this dissertation, I characterize TIL-Bs and identify their cognate antigens in Merkel cell carcinoma (MCC) to understand the question: what is an antigen to the adaptive immune system in the TME? MCC is a rare and aggressive neuroendocrine carcinoma of the skin caused by either Merkel cell polyomavirus (MCPyV) in virus-positive MCC (MCCP) or by high UV damage in virus-negative MCC (MCCN). Approximately half of patients with advanced or metastatic disease respond to immunotherapy (anti-PD1/PD-L1) as a first-line treatment regardless of viral status, suggesting strong immune activation within the TME. Recent studies in MCC identified that TIL-Bs correlate with immunotherapy response and are associated with tumor control. To investigate TIL-Bs in MCC, I combined publicly available MCC single-cell RNA sequencing (scRNAseq) datasets with my own dataset to create an MCC TIL-B dataset with 44 samples and 12,402 cells. Memory B cells make up the largest proportion of TIL-Bs in MCCP and MCCN and show strong evidence of a germinal center-derived response. I also identified that the proportion of plasma cells is significantly higher in responders to immunotherapy, suggesting antibodies could be assisting in the immune response to MCC.

To determine the antigen specificity of TIL-Bs, I recombinantly expressed and characterized 36 antibodies from B cell receptors of TIL-Bs from an MCCP patient biopsy. Flow cytometry and immunoprecipitation mass spectrometry revealed most antibodies bound intracellular proteins that consisted of known autoantigens and one tumor-associated antigen. Known autoantigens consisted of tRNA synthetases, p97/VCP and RNA-binding proteins. These antibodies were derived from plasma cells and had evidence of moderate to high levels of somatic hypermutation (SHM), suggesting they were derived from a germinal center response. I further validated that several RNA-binding proteins, SND1 and DNA-PKcs, targeted by antibodies with high SHM were localized to the cell surface in MCC. This finding supports a potential mechanism for how autoantigens that are mostly characterized as intracellular could be exposed to TIL-Bs.

Lysine-specific demethylase 1 (LSD1)-CoREST is an essential epigenetic regulator complex in MCCP that is transactivated by the viral oncoprotein small T antigen. This complex restricts neuroendocrine differentiation to maintain tumor identity and is a therapeutic vulnerability. I identified 2 distinct clonally expanded antibodies from plasma cells with low SHM that recognized LSD1-CoREST in complex with myelin transcription factor 1 (MYT1). These antibodies also shared the same V gene on the heavy chain (\textit{IGHV6-1}, V\textsubscript{H}6-1) and light chain \textit{(IGKV1-33}, V\textsubscript{K}1-33), which in combination with low SHM suggests a convergent, germline-encoded response to endogenous antigen. To further validate this observation, I used TRUST4 on my TIL-B dataset to computationally derive antibodies and performed BCR sequencing on additional patient tumor biopsies, selecting for antibodies with the V\textsubscript{H}6-1/V\textsubscript{K}1-33 pairing that ranged from low to high SHM. This resulted in the discovery of 5 additional antibodies, 1 computationally derived and 4 from BCR-seq, that recognized MYT1-LSD1-CoREST from 3 distinct MCCP tumor samples. This demonstrates that MYT1-LSD1-CoREST is a tumor-associated autoantigen that elicits a convergent B cell response in MCCP.

In summary, this work challenges what constitutes an antigen in the TME and how TIL-Bs respond to these antigens. I show that germinal center-derived TIL-Bs target classical intracellular autoantigens and a novel tumor-associated autoantigen important for maintaining MCC identity, suggesting positive selection for autoantibodies in the TME that may contribute to anti-tumor immunity.

A hallmark feature of adipose tissue as a central metabolic organ is its capacity for expansion and remodeling in response to physiological demand, with roles beyond simply serving as lipid storage. One striking form of this remodeling is beige or brown-like adipogenesis, the process by which thermogenically active adipocytes arise within white adipose depots in response to cold or adrenergic stimulation, increasing the capacity of the tissue for non-shivering heat production. Integral to this beige adipogenesis, and tissue plasticity as a whole, is the adipose vasculature, which facilitates oxygen, nutrient, and lipid exchange in accordance with local and systemic metabolic state. In response to cold or adrenergic stimulation, beige adipocyte biogenesis is accompanied by increased microvascular growth in inguinal white adipose tissue (iWAT), yet whether this angiogenic response is driven by the beige adipogenic program itself or reflects an independent endothelial response to adrenergic stimulation remained unknown. Here, our central goal was to define the spatiotemporal dependencies between beige adipogenesis and angiogenesis and to identify the molecular signals that coordinate vascular outgrowth within the thermogenic niche.

A major limitation in studying the spatiotemporal organization of adipose tissue remodeling has been the reliance on traditional two-dimensional imaging, which fails to capture the finer details of the adipose tissue which is highly heterogenous. To overcome this, we employed Adipo-Clear, a whole-tissue clearing approach that enables visualization of the intact adipose microvasculature in three dimensions. We found that blunting beige adipocyte biogenesis, whether by disrupting adipocyte lipolysis, thermogenic transcriptional programming, or de-novo beige progenitor differentiation, significantly suppresses cold-induced angiogenesis in iWAT, while leaving the visceral depot unaffected. The pro-angiogenic signal was shown to be lipid-borne and its release was ATGL-dependent. Linoleic acid emerged as the key mediator: it accumulates selectively in cold-exposed iWAT, is depleted when lipolysis is disrupted, and is sufficient to drive endothelial proliferation and tube formation. Mechanistically, we found that these endothelial effects are transduced through COX2-dependent prostaglandin synthesis and EP2 receptor signaling, suggesting that a single lipolysis-derived lipid coordinates both progenitor expansion and vascular remodeling within the thermogenic niche.

Together, these data define a paracrine lipid circuit linking cold-activated adipocyte lipolysis to angiogenic remodeling of the iWAT vasculature. Identification of this axis advances our understanding of how beige adipose tissue remodeling is coordinated at the tissue level and opens new avenues for therapeutic strategies targeting the thermogenic adipose niche in the context of metabolic disease.

As civic and political engagement becomes increasingly visible in the professional sphere, whether through résumés, professional networking platforms, social media, or other digital traces, organizations are more likely to encounter individuals with observable histories of social activism. Yet research has devoted far more attention to understanding how activism influences organizations than to how organizations evaluate individuals who engage in it. This dissertation addresses that gap through two empirical studies and one theoretical chapter. First, a résumé audit study across six U.S. labor markets shows that job seekers with activist backgrounds face a labor-market penalty relative to otherwise identical non-activists. This activism penalty is concentrated in states with political environments hostile to activism. Second, a survey experiment with individuals with hiring experience identifies the mechanisms underlying this penalty: activist applicants are evaluated less favorably primarily because they are expected to create workplace disruption rather than because they are perceived as less competent. The survey experiment further demonstrates that individual political ideology shapes employer evaluations. Building on these findings, this dissertation develops an integrative theoretical framework explaining how organizations construct meaning from activist backgrounds. I argue that activist backgrounds function as expressive, value-laden signals that generate competing trait inferences, which organizational evaluators interpret through perceived value congruence. Ultimately, this dissertation establishes activist backgrounds as a previously understudied object of organizational evaluation and shows why the same activist can be seen as either a changemaker or a troublemaker.