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APOBEC3A Promotes the Metastatic Progression of High-grade Serous Ovarian Carcinoma by Altering Epithelial-mesenchymal Trajectories
No full textHigh-grade serous ovarian cancer (HGSOC) is the most prevalent and aggressive histological subtype of ovarian cancer, and often presents with metastatic disease. The drivers of metastasis in HGSOC remain enigmatic. APOBEC3A (A3A), an enzyme that generates mutations across various cancers, has been proposed as a mediator of tumor heterogeneity and disease progression. However, the role of A3A in HGSOC has not been explored. We observed an association between high levels of APOBEC3-mediated mutagenesis and poor overall survival in primary HGSOC. We experimentally addressed this correlation by modeling A3A expression in HGSOC which resulted in increased metastatic behavior of HGSOC cells in culture and distant metastatic spread in vivo, which was dependent on catalytic activity of A3A. A3A activity in both primary and cultured HGSOC cells yielded consistent alterations in expression of epithelial-to-mesenchymal transition (EMT) genes resulting in hybrid EMT and mesenchymal signatures, providing a mechanism for their increased metastatic potential. Inhibition of key EMT factors TWIST1 and interleukin-6 (IL-6) resulted in mitigation of A3A-dependent metastatic phenotypes. Our findings define the prevalence of A3A mutagenesis in HGSOC and implicate A3A as a driver of HGSOC metastasis via EMT, underscoring its clinical relevance as a potential prognostic biomarker. Our study lays the groundwork for the development of targeted therapies aimed at mitigating the deleterious impact of A3A-driven EMT in HGSOC
Functional and Structural Connectivity as Predictors of Long-term Motor Development in Very Preterm Children with and without Brain Injury
No full textPreterm 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
Novel Therapeutics for Alzheimer\u27s Disease
No full textClinically, Alzheimer’s disease (AD) causes progressive decline in memory and cognitive function which ultimately leads to death. Given that this disease affects 1 in 8 Americans over the age of 65, there is a dire need for a better understanding of the underlying pathology of AD. Recent genetic studies have highlighted the central role of the innate immune system in AD by identifying several risk variants in genes that are predominantly expressed within microglia in the brain. Most notably, rare variants, such as the R47H, R62H and H157Y mutations, in the Triggering Receptor Expressed on Myeloid Cells 2 (TREM2) gene increase risk for late-onset AD (Guerreiro et al. 2013). TREM2 is a cell surface receptor expressed specifically by microglia in the brain. TREM2 signaling occurs through the immunoreceptor tyrosine-based activation motif (ITAM)-containing adaptor DAP12 and its function supports diverse processes such as phagocytosis and clustering around debris, increased metabolic function, and lipid metabolism (Wang et al. 2015). Mounting evidence suggests that TREM2 function is age, context, and disease dependent and highlights the importance of understanding the type of pathology and pathology severity in the brains of patients with AD when therapeutically targeting TREM2 function. Further studies will be necessary to elucidate the effects of TREM2 variants and targeting TREM2 function within the context of Aβ-induced tau seeding and spreading as well as in the phase of tauopathy that is closely linked with neurodegeneration. Using a mouse model of Aβ amyloidosis (5XFAD) in which AD-tau is injected into the brain to induce Aβ-dependent tau seeding/spreading, we found that chronic administration of an activating TREM2 antibody increases peri-plaque microglial activation but surprisingly increases peri-plaque NP-tau pathology and neuritic dystrophy, without altering Aβ plaque burden. Additionally, through use of a 5XFAD/T2CV amyloidosis mouse model expressing the human TREM2 gene injected with AD-tau, we found that chronic administration of an anti-human TREM2 agonist or an anti-human TREM2 antagonist surprisingly both increased NP-tau pathology, total amyloid pathology and changed microglial reactivity in a sex and brain region dependent manner. Finally, I assessed the effects of another novel therapeutic approach for AD, xenon inhalation, on neurodegeneration, tau pathology, and neuroinflammation. As xenon inhalation is being explored in clinical trials as a potential therapeutic in various neurological conditions and neurodegenerative diseases, further understanding of the effects of xenon inhalation is important. We found that xenon inhalation reduced brain atrophy, rescued dentate gyrus layer thickness, improved nest building behavior but did not affect phosphorylated tau accumulation or disease specific conformational modification of tau. We found that astrocytes and microglia were less reactive and moreover, RNA sequencing revealed increased expression of neuronal and synaptic genes and decreased expression of inflammatory genes. Xenon inhalation compared to control air inhalation resulted in a neuroprotective effect, reduced the expression of inflammatory genes, and increased the expression of neuronal and synaptic genes in a mouse model of tau-mediated neurodegeneration. The studies demonstrate that effects of TREM2 and microglia are context dependent and differ based on disease severity, brain region, age, sex, mutation type and the types of pathologies present. All these factors need to be better studied and considered when designing TREM2 and microglial targeting therapies such as xenon inhalation with the goal of mitigating AD and other CNS disease associated pathologies. Prior to moving treatments into clinical trials, it is imperative to understand the effects of various therapeutics based on disease context
A Subset of Senescent Myofibroblasts Orchestrates Immunosuppression in Pancreatic Cancer.
Full text linkPancreatic Ductal Adenocarcinoma (PDAC) is the most lethal solid malignancy with a 12% 5-year survival rate. Most tumors are detected at metastatic stages that are extremely resistant to therapy. PDAC recalcitrance is driven by a unique tumor microenvironment (TME) comprising dense collagenous fibrosis embedded with an abundance of cancer associated fibroblasts (CAFs) and infiltrating leukocytes. Preclinical studies have indicated that PDAC CAFs can have both pro- and anti-tumorigenic effects. This is likely owed to CAF phenotypic heterogeneity which was recently uncovered by single cell transcriptomics. Three major CAF subpopulations have been identified in mouse and human PDAC thus far: myofibroblastic (myCAF), inflammatory (iCAF), and antigen presenting (apCAF). Intriguingly, several studies have also identified PDAC CAF subsets with immune modulatory functions. However, the specific impact and phenotypic drivers of CAF heterogeneity in PDAC remain to be determined. Senescent CAFs have been shown to regulate fibrosis and anti-tumor immunity in skin and liver cancer models. Their effects are mediated by the senescence-associated secretory phenotype (SASP) comprising context-specific matrix and immune modulatory factors. Although a senescent CAF subset has not been investigated in PDAC, the characteristically harsh fibro-inflammatory pancreatic TME likely triggers senescence stress responses in CAFs. In this study, we identify and characterize a subpopulation of senescent myofibroblastic CAFs (SenCAFs) in mouse and human PDAC. We found that SenCAFs localize near tumors ducts and accumulate with PDAC progression. Transcriptomic characterization of the PDAC SenCAF phenotype revealed a matrisome-rich SASP with putative ECM and immune modulatory functions. We demonstrated that senescent pancreatic fibroblasts are pro-tumorigenic in transplantable PDAC models through a partially T cell dependent mechanism. To assess the impact of senescent CAFs in spontaneous PDAC, we crossed the KPPC genetic model of PDAC (LSL-KRASG12Dp53fl/flPdx1-CRE) with the INK-ATTAC (p16/INK4a Apoptosis Through Targeted Activation of Caspase) senescent cell depletion model. Senescence depletion with the KPPC-IA model or the senolytic drug ABT263/Navitoclax, delayed tumor progression, reduced fibrosis, and relieved immune suppression in macrophages and T lymphocytes. Our findings demonstrate that SenCAFs promote PDAC progression, fibrosis, and immune cell dysfunction. Modulating CAF senescence could be utilized clinically to shape a more permissive PDAC microenvironment that enhances immunotherapy efficacy
Mental Health Challenges in Later Life
Full text linkAlthough older adults are less likely to be diagnosed with mental health challenges than younger adults, Americans over the age of 65 have experienced the greatest growth in new diagnoses — an increase of 57% between 2019 and 2023. By 2023, about 1 in 7 adults age 51 and older had received mental health diagnoses, including major depressive, generalized anxiety, adjustment, bipolar, and mood disorders. However, older adults are less likely to receive treatment than younger people. At the same time, older adults may also misuse substances such as alcohol, tobacco, cannabis, and prescription and nonprescription medications. Americans age 75 and older also have higher rates of suicide than any other age group
Coming of Age in the Ancient Andes: A Bioarchaeological Evaluation of Adolescence, Puberty, and Gender in Late Pre-Hispanic Andean Society (800-1400 CE)
No full textThis dissertation uses bioarchaeological methods to examine adolescent development among Tiwanaku and Estuquiña populations from the South-Central Andes (8th–14th c. CE). The study analyzes 217 human skeletal remains and associated burial goods from three sites (Omo M10, Estuquiña M6, and Chen Chen M1) housed at the Museo Contisuyo in Moquegua, Peru. As the first systematic exploration of pre-Hispanic adolescence in the Americas, this research provides new insights into the pubescent life experience in the ancient Andes. The project distinguishes between biologically mature and pubescent individuals, a critical step in establishing social age categories, while examining the interplay between health, development, and cultural systems. By considering different circles of context and their associated energetic factors, this work sheds light on how embodied experiences of adolescence were shaped by both internal biological processes and external cultural expectations. Results challenge prevailing assumptions about the onset and pace of pubertal timing in the past, including the onset of female fertility and reproduction. Additionally, correlations between osteological and archaeological data suggest varying population-level categorizations of personhood related to age and gender
Action-as-Language: Using AI to Model Behavioral Patterns and Context from EHR Workflows
No full textElectronic Health Records (EHRs) have transformed clinical care by enabling structured documentation and streamlining workflows. Characterizing the patterns of EHR use has relied on methods that treat actions as isolated events, limiting the ability to study the sequential dependencies that shape behavior. Modeling clinician EHR action sequences through the lens of a structured language—an approach inspired by prior work in human-computer interaction on the sequential and grammatical nature of user behaviors—offers a novel framework to capture the temporal and structural dependencies within workflows. This dissertation introduces the action-as-language framework and presents a three-part investigation into representing, quantifying, and modeling the structure of clinician behavioral patterns using various structured language modeling techniques. In Aim 1, I develop structure-sensitive sequence representations of EHR interactions to examine how patterns of interaction structure reflect clinical workflows. I apply frequency-weighted statistics and embedding techniques that capture action co-occurrence, evaluating their ability to distinguish work patterns across care settings. Findings show that even simple frequency-weighted representations can differentiate workflows, and embedding-based representations reveal clusters of tasks that align with known clinical activities. These results support the feasibility of using natural language-inspired methods to model clinical behavior in EHR use. In Aim 2, I introduce a novel metric—action entropy—derived from behavioral patterns to quantify the variability and cognitive effort in clinician behavior. By training a custom transformer-based model on directional progression of actions, I estimate how predictable or routine each action is based on learned interaction patterns. Initial validation in known high cognitive-effort scenarios shows significant increases in action entropy between cases and matched controls, suggesting its value as a proxy for cognitive effort in complex workflows. Finally, in Aim 3, I develop and evaluate a general-purpose modeling pipeline for clinician action sequences using large language models (LLMs). This pipeline is designed to learn from EHR action sequences using both symbolic and semantic representations, and is evaluated through two experiments: (1) next-action prediction to evaluate model learning of interaction patterns, and (2) wrong-patient error prediction to test its utility for detecting safety-critical events. Results show that the LLM-based approach more accurately predicts subsequent actions. However, all evaluated approaches—including both traditional and LLM-based models—perform poorly in detecting wrong-patient errors. This suggests that even though language models better capture sequential structure and variability in clinician actions, wrong-patient errors may be influenced by factors beyond what is encoded in prior EHR interactions. Collectively, this dissertation presents the action-as-language framework as a novel approach for understanding clinician behavior through structured language modeling. By capturing structural patterns in EHR action sequences, quantifying behavioral variability, and modeling sequential dependencies, this work lays the groundwork for future efforts to study clinical workflows, cognitive demands, and clinician interaction with EHR systems
Montane β-diversity: Biodiversity through Space and Time in Earth’s Most Biodiverse Regions
No full textMontane ecosystems represent some of Earth’s most ecologically complex regions in the world, harboring a disproportionate number of endemic species. For example, they comprise 25% of all land area, yet 87% of all terrestrial biodiversity can be found in them. Temperature, precipitation, and other abiotic factors change dramatically across short geographic distances in montane ecosystems, providing unique opportunities to study how communities assemble across space and time. Understanding how biodiversity is structured in montane ecosystems is, in many ways, a window into understanding how biodiversity is structured more broadly — making it not only a question of theoretical importance, but also one of urgent conservation relevance in the face of accelerating global change. While decades of research have explored patterns of species richness (alpha-diversity) across elevations, much less is known about beta-diversity. Beta-diversity captures the extent of species turnover or community differentiation across space or time and can provide insights into the processes of community assembly. My dissertation aims to address this gap through three goals: 1) assess how community composition of small mammals in California’s Sierra Nevada mountain range has changed over the past century in response to climate change, using historical resurveys, 2) evaluate patterns of within-elevation beta-diversity in forest tree communities across 38 ecoregions in temperate North America, and to test how these patterns are shaped by regional species pools and local assembly processes, and 3) test the Ecotone Hypothesis by conducting a global synthesis of avian turnover across elevations, using a null model approach to identify where turnover is higher than expected under random assembly. In chapter 1, I test whether small mammal communities in California’s Sierra Nevada have shifted in community composition over time in favor of more warm- and dry-adapted species across three transects distributed across the northern, central, southern regions of the mountain range. I found that communities have shifted directionally toward more warm- and dry-adapted species in the southern region, but not the northern and central regions. Importantly, changes in community structure in all three regions lagged behind corresponding changes in climate. These widespread lags between community composition and shifting temperature and precipitation regimes indicate that many communities are already out of equilibrium with their environments, increasing their vulnerability to future warming and drying. In chapter 2, I synthesized within-elevation beta-diversity patterns of tree communities from 38 mountainous ecoregions spanning the coterminous United States and performed a null model analysis aimed at disentangling the relative roles of regional sampling effects and local assembly mechanisms on these patterns. I found that beta-diversity after controlling for regional species pool size – i.e., beta deviations – does not exhibit consistent elevational patterns across ecoregions. This suggests the effects of local community assembly mechanisms are region-specific. These results underscore the need for region-specific management strategies that account for the interplay between regional species availability and local assembly processes, rather than relying on one-size-fits-all expectations for community responses to environmental gradients. In chapter 3, I test the ecotone hypothesis in 40 montane regions around the world using a null model analysis that randomizes bird species ranges while preserving range structure. I show that on average, half of the elevational transitions within mountain ranges showed greater compositional turnover than expected under the null model. The proportion of elevational bands exceeding null expectations was positively associated with mountain range area, elevational extent, and species richness, suggesting that topographically and biologically complex systems are more likely to exhibit non-random community turnover. These findings suggest that ecotones play a key role in structuring bird communities worldwide, and that shifts in their position or permeability could precipitate rapid, spatially concentrated reorganizations of avian assemblages. Collectively, these findings advance our understanding of how beta-diversity is structured in montane systems, how it varies across space and time, and how it reflects underlying ecological and evolutionary processes. By integrating resurvey data, national forest inventories, and global biodiversity datasets, this dissertation contributes to a more nuanced understanding of community structure in mountains—one that is essential for predicting biodiversity responses to environmental change
Wavelet Representation of Singular Integral Operators
Full text linkThe idea of representing singular integral operators as averages dyadic shifts has proven fruitful since Petermichl\u27s representation of the Hilbert transform, and its generalization by Hyt\ onen to prove the conjecture. These results employ a random dyadic decomposition of the operator in terms of Haar shifts of all complexities. An alternate approach to wavelet representation was provided by Di Plinio, Wick, and Williams (2022) in which the random dyadic grids are replaced by zero-complexity wavelet projections, providing finer control of smooth operators and a more efficiently computable representation. The goal of this thesis is to provide two main generalizations of this continuous representation theorem; Both results are new and permit broader applications of the wavelet representation. First, we loosen the smoothness required of the Calder\\u27on--Zygmund operators to be Dini-type. This strengthens even the original statement for H\ older moduli of continuity by improving the loss of smoothness of the adapted wavelets to be precisely double-logarithmic. In general, the double log-Dini condition is likely not sharp, but is essential to the construction of a representation from wavelet averaging. We also consider operators in the ambient setting of spaces of homogeneous type, using wavelets adapted to dyadic grids constructed by Auscher and H\ ytonen. Because of the purely geometric nature of such spaces, this statement is made only in the case of fractional-order smoothness. Consequently, the statement is purely -type, which is still sufficient for proving new applications applications such as representations for compact Calder\\u27on-Zygmund operators
Universal Asset Building: New Social Policy for a New Era
Full text linkThis Perspective explores the concept of universal asset building, beginning with Child Development Account policy, as a new paradigm in social policy, suggesting that it will be a positive social-policy strategy for navigating the information age, and especially artificial intelligence (AI). Universal asset building can address social and economic challenges posed by rapid technological advancements.
The Perspective is adapted from a keynote address given by Michael Sherraden (with Jin Huang and Li Zou) at the joint convening of the 2024 Annual Academic Conference for the Social Policy Research Committee of the Chinese Sociological Association and the 19th International Symposium on Social Policy. The convening was held in Shanghai at Fudan University, December 7–8, 2024