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Intimate Partner Violence and Dementia Risk: Challenges and Opportunities for Longitudinal Studies of Aging
No full textBy 2060, the burden of Alzheimer’s disease and related dementias (ADRD) in the U.S. is expected to double to 13.9 million, with women being overrepresented among cases. However, many powerful aspects of women’s lives–including exposure to gender-based violence–have received almost no attention in ADRD research. Women’s exposure to gender-based violence, particularly intimate partner violence (IPV), is pervasive though; nearly 30% of older women have experienced IPV in their lifetime.
Thus, this dissertation investigates the long-term, aging-related health consequences of IPV among women relevant to ADRD risk by evaluating (1) the overall scientific premise that experiences of IPV have deleterious impacts on ADRD risk using trajectories of midlife cognitive functioning, (2) whether earlier and greater burdens of trauma over the life course have disproportionately deleterious impacts, and (3) whether the estimated impacts of IPV on ADRD-relevant health outcomes are greater in magnitude in a more racially and socioeconomically diverse, population-representative sample. To do so, this dissertation examines both common methodological challenges and novel substantive inquiry via measures of exposure to intimate partner violence, longitudinal assessments of cognitive functioning and cardiovascular disease, and/or measures of childhood and adulthood trauma in Nurses’ Health Study II (NHS2) and in Health and Retirement Study (HRS).
More specifically, Chapter 2 first evaluates the nature and magnitude of potential practice effects, changes in test performance due to repeated cognitive assessments, utilizing availability of randomized follow-up schedules in NHS2, an important threat to internal validity among studies of longitudinal cognitive functioning. Chapter 3 then focuses on estimating associations between exposure to IPV experiences and trajectories of midlife cognitive functioning among women in NHS2. Chapter 4 subsequently evaluates if experiences of childhood abuse modify the associations observed between IPV and cognitive functioning in NHS2 to understand how interpersonal violence across individual lifecourse impacts cognitive health. Chapter 5 then utilizes a novel application of causal inference methods to attempt to quantify the population-level impacts of IPV experiences on long-term health outcomes relevant to ADRD risk, accounting for differences between the highly selected study sample (NHS2) and a sample of a relevant US target population (HRS). Chapter 6, in recognition of the necessity for measurement of IPV in longitudinal aging cohorts to overcome challenges presented in Chapters 3-5, concludes the dissertation via a shorter commentary discussing drivers of the paucity of epidemiological evidence on traumatic experiences.
Altogether, this dissertation highlights the importance of gendered social experiences in shaping observed trajectories and inequalities in long-term health outcomes relevant to ADRD risk and argues for improved methodological approaches to inquiry as well as critical measurement of these relevant constructs in longitudinal aging cohorts as a primary starting point
Task-Dependent Mouse Behavioral Dynamics in Navigational Decision-Making
No full textEffective navigation in their environment requires animals to process and integrate diverse inputs across varying timescales while adaptively responding to their surroundings. This ability to integrate information over a diversity of timescales is fundamental to perception, cognition, and motor planning. However, behavioral responses are influenced not only by external inputs but also by experience, expectation, and internal cognitive states. Understanding neuronal computations in the brain, especially regarding complex higher-order cognitive processes, requires a comprehensive characterization of animal behavior that allows us to meaningfully interrogate the neural circuits underlying them. In this work, we have developed a complementary set of behavioral paradigms designed to isolate task-dependent cognitive processes from external inputs by imposing distinct temporal demands while ensuring that sensory stimuli and required behavioral outputs are as similar as possible between tasks. We trained mice to perform three navigational decision-making tasks based in visual virtual reality and established tools to quantify their behavior. We showed that animal running speed was modulated by task context and that training history impacted decision-making strategies. Moreover, we identified behavioral variabilities that were suggestive of latent cognitive states, such as confidence and indecision. Finally, by analyzing running trajectories and employing behavioral modeling approaches, we inferred timescales of choice formation aligned with the presentation of task-relevant stimuli. Our novel behavioral tasks, which can be combined with the extensive genetic and optical techniques that have been developed for rodents, are thus valuable tools for the study of the temporal dynamics of information integration and perceptual decision-making, facilitating deeper insight into the underlying neural circuits.Medical SciencesMedical Science
Speaking Like The State: Political Economy of Language Planning in Turkey
No full textBetween 1932 and 1938, the Turkish government undertook a campaign of linguistic purification, known as the Turkish Language Revolution, which drastically changed the etymological composition of the Turkish language. In this paper, I construct a novel text database of 340 million words covering 90 years to quantify the change in preference from Perso-Arabic to Turkic vocabulary. My dataset indicates that the share of Turkic vocabulary increased by more than 20 percent at the expense of Perso-Arabic vocabulary in the first 50 years after the Revolution, but I also document a statistically significant increase in the usage of Perso-Arabic vocabulary in recent years at the expense of Anglo-French vocabulary, a reversal of the goals of the Language Revolution. My analysis, using event studies, disentangling word-level heterogeneous treatment effects and analyzing diversity of words in the newspaper, shows that the Revolution succeeded not as an incidence of top-down centralized planning by the Kemalist establishment, but in so far as it responded to the demands of writers and intellectuals, suggesting that the pen is indeed mightier than the sword
"If I see another palm tree, I will have a conniption!": Re-presenting Hospitality Landscapes in Jamaica
No full text...Indeed, almost from the inception of tourism industries on the islands, hoteliers, colonial administrators, and local white mercantile elites (re)created or tropicalized many aspects of the islands precisely in the image of these representations. They physically transformed areas of the islands through planting campaigns or cleanliness drives, in efforts to make the islands appear as they did in photographs—orderly, picturesque, and tropical.
Krista A. Thompson, An Eye for the Tropics: Tourism, Photography, and Framing the Caribbean Picturesque, Objects/Histories (Durham: Duke University Press, 2006). 40.
This thesis re-presents the image of the tropics at the site of the hotel, a “space where ideals of the picturesque tropical landscape were re-created in miniature” (Thompson 2006, 1). To do so, it draws upon the vernacular landscape of the Jamaican yard, embracing its public-private spatial logic and botanical diversity, to propose a hotel landscape that renders visible the lifeways, natural heritage, and the people of the island
Biochemical diversity of interferon signaling pathways in innate immunity
No full textInnate immune cells within mammalian organisms function as the first line of defense against infectious threats. Phagocytes, such as macrophages, respond to microbial insults by sensing pathogen-associated molecular patterns (PAMPs) via pattern recognition receptors (PRRs) and activating downstream signal transduction proteins. These signaling pathways are tightly regulated to trigger various inflammatory responses, which activate the adaptive immune system and promote the resolution of infection or damage. The host interferon response represents one such system that is central to antiviral immunity. The expression of type I interferons is governed by upstream PRRs that nucleate oligomeric supramolecular organizing centers (SMOCs) via adaptor proteins including STING, TRIF, and MAVS. These adaptors utilize a conserved pLxIS motif to activate the downstream kinase TBK1 and transcription factor IRF3.
Apart from the established roles of STING, TRIF, and MAVS in IRF3 activation, the existence of additional pathways and functions associated with the pLxIS motif is unknown. Leveraging a synthetic biology-based platform to isolate and dissect pLxIS motif activities, we revealed an unexpected diversity and specificity in signaling mechanisms. This system enabled us to identify two orphan proteins that utilize pLxIS motifs, in conjunction with contiguous motifs in the same domain, to stimulate interferon responses independently of the established pathways. These two proteins, IRSp53 and GMIP, may regulate interferon signaling pathways within fibroblasts. Another interferon adaptor protein, TASL, employs an alternative mechanism whereby its pLxIS motif is physically separated from the requisite kinase activation motif downstream of MyD88. Further mechanistic analysis uncovered variable functions of each pLxIS-containing domain in activating IRF3, the TRAF6 ubiquitin ligase, IκB kinases, mitogen-activated protein kinases, and metabolic activities. This diversification enabled subsets of pLxIS-containing proteins to confer protection against viral infection in human cells.
Overall, these collective findings establish pLxIS-containing domains as commonly used and biochemically flexible regulators of interferons and metabolism. They furthermore underscore the value of synthetic biology as a tool to discover additional regulators of innate immunity.Medical SciencesMedical Science
Mathematical and Computational Modeling of Suicidal Thoughts and Behaviors
No full textSuicide is one of the most devastating, complex, and perplexing of all human behaviors. Unfortunately, despite centuries of scientific inquiry, suicidal thoughts and behaviors remain exceedingly difficult to understand, predict, and prevent. This dissertation aims to develop and integrate methods from across the clinical and computational sciences, with the goal of advancing our ability to capture and model the immense complexity of suicidal thoughts and behaviors. Paper 1 harnesses recent advances in real-time monitoring technology to monitor patients’ momentary suicidal thoughts during psychiatric hospitalization, and models dynamic fluctuations in these data to predict suicide attempts during the high-risk time period following hospital discharge. Paper 2 takes an idiographic approach, building personalized machine learning models to predict suicidal thoughts as they unfold in the real world, in real time. Paper 3 takes a complementary theory-driven computational approach to construct and evaluate a formal mathematical model of suicide as a dynamical system, using systems of differential equations. Together, findings from this dissertation suggest that real-time monitoring data can advance our ability to predict suicidal thoughts and behaviors (at both the group and individual level), particularly when combined with data-driven computational methods such as machine learning. In addition, this dissertation demonstrates the promise of formal mathematical modeling in advancing the understanding of suicide, by allowing for direct observation of a theorized system’s behavior over time. Future directions for both data- and theory-driven computational methods in suicide research are presented in the general discussion
Building and maintaining the ultrastructure of Plasmodium falciparum parasites during the asexual blood stage.
No full textApicomplexan parasites exhibit great diversity in cellular and subcellular morphology that is key to
their ability to infect diverse host species and target cells. The study of this distinctive cell biology is often
hindered by the small size and complex lifecycles of these organisms. This is especially true in the study
of Plasmodium parasites, the causative agents of malaria. This thesis surveys the changing ultrastructure
of Plasmodium falciparum during its asexual blood stages using cutting-edge microscopy techniques, and
uses molecular methods to characterize cytoskeletal structures and protein-protein interactions
responsible for building and maintaining this ultrastructure.
In Chapter 2, we apply ultrastructural expansion microscopy (U-ExM) to describe the three-dimensional organization of P. falciparum parasites in the asexual blood stages. We catalogue 13
different P. falciparum structures and organelles across the intraerythrocytic development of this parasite
with a focus on schizogony, the simultaneous division of a parasite into dozens of daughter cells. We use
this dataset to trace the biogenesis and organization of each of these 13 structures, shedding light on
multiple poorly understood but fundamental aspects of P. falciparum cell biology.
The cytoskeleton of Plasmodium parasites is essential for cell structure, replication, motility, and
infectivity. P. falciparum leverages a divergent family of cytoskeletal proteins known as alveolins to meet
some of these diverse needs. In Chapter 3, we demonstrate that the alveolin PfIMC1g (PF3D7_0525800)
is essential for P. falciparum asexual replication. We characterize nonviable PfIMC1g-deficient parasites
and hypothesize that the primary role of PfIMC1g is to maintain structural integrity, protecting parasites
from incurring damage during the process of invasion. We also report new findings on the architecture of
Plasmodium alveolins, including an interaction between PfIMC1g and 1c and the localization of PfIMC1e
and 1f to the basal complex.
In Chapter 4, we extend our characterization of alveolin architecture and essentiality to map how
these proteins are recruited to the parasite cytoskeleton. Specifically, we characterize alveolin-alveolin
interactions mediated by the alveolin domain conserved within this family. We find that blood-stage
alveolins have variable dependence on their alveolin domains and alveolin binding partners for function
and localization.
Overall, this work provides a more detailed picture of how P. falciparum parasites organize their
cytoplasmic contents during cell division, along with an in-depth analysis of cytoskeletal structures
assembled during this process to protect parasite integrity. Our study of alveolin function and dissection of
relevant domains is the first of its kind in Plasmodium and will increase our understanding of these unique
filaments, whose physiological importance and divergence from human proteins make them candidates
for future drug development.Medical SciencesMedical Science
AI for single-cell multi-modality biology
No full textCells are the fundamental building blocks of all life on Earth. All cell types of one organism, despite sharing the same genetic blueprint, undertake distinct cellular fates guided by underlying molecular networks. These networks, encompassing gene transcription, translation, and their intricate intra- and extra-cellular interactions, regulate and delineate cellular function, identity, and fate. Understanding the spatial-temporal dynamics of these molecular regulatory networks and their impact on cellular functions is pivotal for understanding development, disease onset, and aging. With the advancement of single-cell multi-modality measurement technologies (e.g., scRNA-seq, patch-seq), we are now able to capture an unprecedented level of detail from individual cells from molecular to functional level. However, this influx of data, laden with intricate information about diverse molecular interactions, presents an analytical challenge that traditional methods struggle to address comprehensively. AI, with its capability to discern complex non-linear patterns in high-dimensional datasets, holds great promise to illuminate these complexities. Yet, its prevalent black-box nature obscures confidence in AI-derived insights. Moreover, current analytical methods are designed to perform a single task, only providing a partial picture of the multi-modality data. In this thesis, I focus on introducing single-cell multi-modality biotechnologies for gene-to-function mapping and developing explainable and predictive AI models to analyze different modalities of single cells.
First, I review recent progress in flexible electronics capable of tracking the electrical activity in the neural and cardiac systems (Chapter 1). Then, by fusing the flexible electronics with spatially resolved sequencing, I introduce the in situ electro-seq, which allows stable mapping of electrical activity at the millisecond time scale and profiling of gene expression from the same cells across intact biological networks. In addition, I develop machine-learning-based cross-modal analysis to identify gene-to-electrophysiology relationships throughout cardiomyocyte development (Chapter 2). Finally, I focus on predictive and explainable AI models capable of generic analysis for single-cell multi-modality measurements (Chapter 3)
Essays on Emotion and Decision Making, with Implications for Policy
No full textDespite the remarkable growth of the field of emotion and decision-making in recent decades, our understanding of the potential effects of positive emotions and emotion regulation remains limited. This dissertation aims to advance our knowledge on these fronts. Drawing on and extending the insight that appraisals (i.e., patterns of interpretations) shape emotion experiences and are fruitful targets for regulating emotions, three essays elaborate on how emotions and their regulation influence judgment and decision-making in diverse domains.
The first essay provides novel insights into the relationship between positive emotions and health decision-making, updating prior meta-analytic conclusions that positive emotions have no protective effects on appetitive risk behaviors. Drawing on and extending the Appraisal Tendency Framework, this essay proposes that gratitude, but not all positive emotions, could diminish decisions associated with cigarette smoking—a leading cause of preventable death globally. A series of multi-method studies provided evidence supporting this hypothesis (collective N = 34,222). Importantly, these findings reveal a missed opportunity in costly public health campaigns, which seldom evoke gratitude. By emphasizing gratitude’s potential role in mitigating appetitive risk behaviors, this work opens new avenues for intervention design in public health.
While gratitude confers many benefits, the second essay offers a more nuanced understanding of the role of gratitude in moral decision-making. Building upon and expanding the Appraisal Tendency Framework, this essay introduces a phenomenon called gratitude-induced collusion, where gratitude could lead decision-makers to bend the rules to benefit others. Two financially incentivized experiments provided evidence supporting the hypothesis (collective N = 2,414). Gratitude increases collusion to benefit not only people who trigger the emotion (where reciprocity is present), but also unacquainted peers (where reciprocity is absent). These results update prior findings concluding that reciprocity has null effects on collusion and that gratitude intrinsically increases honesty. The findings prompt a deeper examination of gratitude's potential role in corruption and consideration of unintended consequences of positive emotion interventions.
Finally, the third essay sheds new light on the role of emotion regulation in stressful work contexts. It hypothesizes that practicing reappraisal (a strategy involving altering one's appraisals about emotionally charged situations) could benefit emotional well-being and workplace outcomes among low-income workers, and a brief, low-cost, scalable reappraisal intervention could achieve durable effects. A survey and a longitudinal field experiment provided evidence supporting this hypothesis (collective N = 4,455). The findings deepen the discourse on boundary conditions, benefits, and costs associated with different emotion regulation strategies. By illuminating, for the first time, brief reappraisal intervention's long-lasting effects among low-income workers, this research underscores its potential to benefit diverse populations.
Taken together, the present work enriches the understanding of the vital roles of emotion and emotion regulation in shaping decisions in health, moral, and organizational contexts. The findings hold significant policy implications for enhancing life expectancy, curbing dishonesty, and fostering workforce well-being
