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Osteoarthritis as a Multi-Factorial Disease: Exploring Piezo Ion Channels and Adipose Tissue as Therapeutic Targets
No full textOsteoarthritis (OA) is a complex disease involving mechanical and inflammatory factors that affect both the joint and systemic environments. Despite its prevalence as a leading cause of pain and disability worldwide, no disease-modifying OA drugs (DMOADs) are currently available. This dissertation focuses on exploring key targets and developing innovative tools to combat OA, addressing its mechanical and inflammatory drivers both independently and in combination. First, we investigated the role of mechanosensitive ion channels Piezo1 and Piezo2 in OA pathogenesis using a murine destabilization of the medial meniscus (DMM) model. Our findings demonstrated that knocking out Piezo1, Piezo2, or both in chondrocytes had significant effects on cartilage integrity, synovial inflammation, and pain. A Piezo1 knockout suggests a potential delay in disease onset, as indicated by pain and behavior data, but ultimately led to severe cartilage damage and heightened synovitis. Meanwhile, a Piezo2 KO showed a sex-specific effect, exacerbating cartilage damage in female mice but reducing pain-related behaviors. Notably, a dual Piezo1 and Piezo2 knockout provided a protective phenotype in male and female mice, reducing cartilage damage, synovial inflammation, and pain, underscoring the compensatory and synergistic roles of these channels in OA progression. Next, we explored the intersection of obesity-induced inflammation and mechanical injury in OA progression. Using a murine model combining DMM surgery and a high-fat diet (HFD), we investigated the role of the mechanosensitive ion channel Piezo1 in obesity-associated OA. Obesity induces a chronic pro-inflammatory state, characterized by elevated levels of adipokines such as IL-6, IL-1α, and leptin, which exacerbate cartilage degradation and amplify mechanical stress responses in chondrocytes. Preliminary findings revealed sex-specific roles for Piezo1 in cartilage protection and pain progression. A Piezo1 knockout reduced inflammation and altered pain behaviors in male and female mice and reduced cartilage damage in female mice, highlighting its critical role in driving the mechanoresponse of chondrocytes in obesity-associated OA. These results emphasize the combined impact of systemic inflammation and abnormal joint loading in OA pathogenesis and suggest that targeting Piezo1 holds promise as a therapeutic strategy to mitigate both structural and symptomatic aspects of OA, particularly in patients with obesity. To further dissect the impact of obesity-induced inflammation on cartilage health, we investigated the interplay between systemic inflammatory mediators and chondrocyte mechanotransduction in a murine diet-induced obesity (DIO) model. By examining both the pericellular matrix (PCM) and extracellular matrix (ECM) of knee cartilage, alongside isolated chondrocytes subjected to adipokines and inflammatory cytokines, we explored the dual influence of metabolic and mechanical factors on cartilage degeneration. While no significant differences in PCM or ECM mechanical properties were observed between HFD-fed and chow-fed mice, the pronounced effects of IL-6 and TNF-α on chondrocyte deformation and calcium signaling highlighted the critical role of systemic inflammation in early cartilage changes. Piezo1 inhibition attenuated these inflammatory effects, emphasizing its role in mediating mechanotransduction under pro-inflammatory conditions. These findings underscore the importance of systemic inflammation in obesity-associated OA and suggest that Piezo1 inhibition could serve as a promising therapeutic strategy to preserve cartilage health in inflammatory environments. Finally, we developed a novel platform for studying adipokine signaling in OA progression. Using genome-edited murine induced pluripotent stem cells (iPSCs), we created genetically engineered adipocytes capable of adipogenic differentiation and in vivo engraftment. These engineered cells allow for precise manipulation of adipokine secretion, enabling the study of adipose-derived signaling in OA and other conditions. Transplantation of these adipocytes into fat-free lipodystrophic mice challenged with DMM surgery provides a robust model to disentangle the roles of individual adipokines in OA progression and test therapeutic strategies. This work advances the field of OA research by identifying Piezo ion channels as critical mediators of mechanotransduction and inflammation in OA, highlighting their potential as therapeutic targets. The integration of diet-induced obesity and joint injury models provides novel insights into the synergistic effects of systemic inflammation and mechanical stress on cartilage health. Additionally, the development of genetically engineered adipocytes offers a transformative tool for studying adipokine signaling and exploring adipose tissue as a therapeutic target. Collectively, this research underscores the multifaceted nature of OA and provides a robust foundation for advancing the development of novel disease-modifying therapies
Noninvasive Assessment of the Tumor Using cfDNA
No full textNext-generation high-throughput sequencing, which is increasingly generating vast amounts of genomic data, offers opportunities for a deeper understanding of the multifaceted nature of cancer and, hence, better patient care. However, the inherently complex and heterogeneous nature of cancer and the significant challenges in the generated data demand advanced data-driven frameworks to decode the molecular underpinnings of cancer. Moreover, the undeniable need for non-invasive approaches presents additional technical challenges in this domain. This dissertation proposes novel frameworks addressing three key challenges in computational oncology. The first study of this dissertation develops a data-driven algorithm to identify stemness signatures in metastatic castration-resistant prostate cancer (mCRPC) plasma cfDNA methylation data utilizing the overall inverse relationship between methylation and gene expression. The second study proposes an efficient, robust, scalable multi-phenotype differentially methylated region (DMR) detection approach. Additionally, this study systematically evaluates deep learning architectures for genomic translation in the context of inferring methylation from urinary cfDNA whole-genome sequencing data. Subsequently, the inferred methylation data is utilized in a cancer classification model to distinguish bladder cancer from healthy samples. Finally, in the third study, a multi-cancer classification framework for genitourinary (GU) cancers based on urine samples is proposed. This framework non-invasively classifies bladder, prostate, and kidney cancers along with healthy samples. The robustness of the framework at varying tumor fractions is validated through in silico simulations. Incorporating sophisticated algorithmic, deep learning, and machine learning approaches, this dissertation proposes frameworks to address three key challenges in advancing non-invasive cancer care. Demonstrating strong performance through extensive experiments, it is intended to serve as an important step toward overcoming current challenges in the development and application of computational methods for cancer management
Impact of Disease-Causing Mutations in TRPV4 and Collagen VI on the Mechanobiology of iPSC-Derived Tissue-engineered Cartilage
No full textChondrocytes, derived from the mesodermal lineage, form a cartilage template that serves as the foundation of the developing skeleton during embryogenesis, and are responsible for maintaining the tissue\u27s homeostasis following post-natal growth. In the process of mechanotransduction, chondrocytes convert mechanical signals into a biophysical, cellular response. Work in this dissertation uses in vitro modeling with human induced pluripotent stem cells (hiPSCs) and transcriptomic analysis to investigate the mechanisms through which cartilage disease-causing mutations influence chondrocyte mechanotransduction, with a focus on physiologic joint loading conditions that activate the mechanosensitive ion channel transient receptor potential vanilloid 4 (TRPV4). TRPV4 plays a crucial role in cartilage development as its mutation is associated with a spectrum of pediatric musculoskeletal diseases. In particular, the V620I mutation leads to brachyolmia, a dysplasia characterized by short stature and skeletal abnormalities, while the T89I mutation is associated with a more severe phenotype of metatropic dysplasia. Both mutations have been linked to disrupting chondrocyte hypertrophy during endochondral ossification, the process of long bone growth. Using in vitro disease modeling facilitated by mechanical loading of tissue-engineered cartilage derived from iPSCs gene-edited with these mutations, we investigated their impact on chondrocyte mechanotransduction. RNA-sequencing analysis identified V620I and T89I mutant tissue-engineered cartilage were both associated with a reduced mechanoresponse. In addition, each mutation was linked to a unique transcriptomic signature, with T89I influencing the immediate, transiently activated loading response, while V620I regulated genes activated after 24 hours. A thorough understanding of the pathways through which the chondrocyte’s mechanoresponse is altered due to these mutations enables the identification of tailored targets for the treatment and prevention of skeletal dysplasias caused by gain-of-function mutations in TRPV4. Osteoarthritis (OA) is a complex, multifactorial disease characterized by the progressive degeneration of articular cartilage primarily due to an imbalance of chondrocyte catabolic and anabolic activities. Exome sequencing studies identified a variant in collagen type VI alpha three (COL6A3), one of the monomeric units forming collagen VI, in a patient with familial OA. COL6A3 encodes for one of the monomeric units forming collagen type VI, a differentiating component of the chondrocyte’s pericellular matrix (PCM). Collagen type VI maintains the structural and mechanical integrity of the PCM, acting as a key regulator for the transduction of chemical and mechanical cues to the chondrocyte. Using gene-edited iPSCs harboring the identified variant, we focused on characterizing alterations in mechanotransduction, in addition to the intrinsic and extrinsic factors regulating chondrocyte physiology, including circadian regulation and sensitivity to proinflammatory cytokines. COL6A3 mutant chondrocytes exhibited impaired TRP4-mediated mechanotransduction, characterized by an elevated osmotically-induced Ca2+ signaling response, and a lower anabolic response to channel activation reflected in gene expression and matrix production. RNA-sequencing identified that COL6A3 mutant chondrocytes dysregulated multiple pathways in response to mechanical loading, and exhibited a TRPV4-dependent difference in their mechanosensitive transcriptional profile. In addition, the variant was associated with disruptions in circadian rhythms, marked by the overexpression and shift in phase of the core clock gene BMAL1. Modeling the inflammatory osteoarthritic joint environment revealed increased chondrocyte catabolism and reduced COL6A3 synthesis in mutant chondrocytes, after challenge with the proinflammatory cytokine interleukin-1 (IL-1). Mutation-mediated effects were likely driven by an altered PCM structural and mechanical composition, reflected by the reduced expression of proteins involved in collagen type VI interactions and matrix organization, in addition to a lower PCM elastic modulus measured by immunofluorescence-guided atomic force microscopy. Finally, we developed a targeted knock-in mouse model harboring the COL6A3 mutation for in vivo modeling of the variant, with the induction of OA to be investigated through surgical, injury-induced, and spontaneous age-related models. Overall, understanding the mechanisms underlying altered mechanobiology due to mutations in TRPV4 and type VI collagen will aid in the development of drug targets for therapeutic strategies and disease prevention
Scaling Quantum Systems: Quantum Networks, Distributed Quantum Computing, and Security
No full textRecent advancements in quantum computing have opened up new possibilities across various fields, offering significant potential to enhance computation, communication, cryptography, and applications in areas like sensing, medicine, and chemistry. However, the capabilities of individual quantum devices are still limited, and scaling quantum hardware monolithically presents substantial challenges. Interconnecting quantum systems offers a promising alternative by aggregating capabilities across a network, thereby enabling quantum advantages for larger and more practical problems. This interconnection is achieved through quantum networking, which links external quantum systems, and Distributed Quantum Computing (DQC), which connects quantum processors within a system, such as in quantum data centers. As the scale of interconnected systems increases, security concerns associated with their integration also grow. To advance quantum networking and DQC techniques, numerous models of quantum repeaters and switches have been proposed, each presenting distinct strategies for enabling quantum communication over long distances. Our focus is on repeaters that leverage entanglement generation and swapping, known as “quantum-native” or “first-generation” repeaters. These repeaters face challenges stemming from the probabilistic nature of entanglement generation and limited coherence times. To address these challenges, this dissertation examines the core principles of quantum networking, DQC, and quantum network security, and presents our contributions to these fields. In particular, we propose Asynchronous Entanglement Routing (AER) to eliminate the need for synchronized operations required by existing approaches and to preserve unused entanglement links, significantly enhancing the efficiency of End-to-End (E2E) entanglement distribution. AER operates in a distributed manner using only local neighbor information for routing, employing structures such as Destination-Oriented Directed Acyclic Graphs (DODAGs) or distributed spanning trees. By mitigating delays caused by network-wide updates, AER significantly improves practicality for quantum applications. Our results demonstrate that AER achieve a higher upper bound and significantly increase the entanglement rate compared to existing synchronous approaches. The practicality and efficiency gains suggest that AER will have a substantial impact on quantum networks as technology progresses. We further extend AER to a multi-tree networking scheme to accommodate larger-scale quantum networks. This approach connects multiple DODAGs in a distributed manner, achieving a higher E2E entanglement generation rate in a practical and asynchronous fashion, while still relying solely on the local knowledge of each node’s entanglement links. Testing on both generated and realistic topologies indicates that the multi-tree approach outperforms single-tree and synchronous routing schemes in terms of entanglement rate and efficiency. This work highlights the effectiveness of asynchronous routing strategies for diverse quantum network topologies and presents a superior routing solution. In addition to interconnecting external quantum systems, the need for linking Quantum Processing Units (QPUs) within a single system has also grown, driving the expansion of DQC architectures. In a quantum data center with multiple QPUs distributed across different racks, executing remote gates requires entanglement between distinct QPUs. However, generating this entanglement often leads to congestion and resource contention. To address this, we propose a resource management framework that maximizes fidelity-guaranteed throughput while maintaining dependencies. We formulate the problem as a Mixed-Integer Linear Programming (MILP) model for benchmarking and introduce efficient heuristic scheduling algorithms. Simulations show that these heuristics closely approximate the solver’s results, demonstrating their practicality for managing remote gates and improving overall performance. Despite the enhanced security that quantum networks offer over traditional systems, the quantum internet still faces unique security challenges crucial for ensuring its Confidentiality, Integrity, and Availability (CIA). We examine these challenges by analyzing vulnerabilities and potential mitigation strategies across different layers of the quantum internet, including the physical, link, network, and application layers. We assess the severity of potential attacks and evaluate the effectiveness of corresponding countermeasures, integrating both classical and quantum approaches. The findings highlight the dynamic nature of security risks and emphasize the need for adaptive security measures. It underscores the need of continuous exploration into the security aspects of the quantum internet to enhance its robustness and facilitate its widespread adoption. We further explore quantum-era cryptographic applications through a theoretical analysis of quantum blockchains for decentralized identity authentication. It includes a proposed conceptual framework, a review of supporting technical evidence, and an evaluation of its core components, feasibility, effectiveness, and limitations
Parapinopsin: a Photoswitchable Inhibitory GPCR for Two-photon Optogenetics
No full textThe development of optogenetic tools has greatly advanced the capability of researchers to understand the connection between neuronal activity and behavior. Optogenetics makes use of opsins, which are light activated ion-channels, ion pumps, or G-Protein coupled receptor (GPCR-based) proteins used to regulate cellular activity. Coupled with technological advances in genetics and optical physics/microscopy, optogenetics can be used to control specific populations of cells in a time-locked, spatially specific manner. The experiments possible with optogenetics depend largely on the capabilities and limitations of the opsin used; thus, there have been continuous efforts to design and employ new opsins with a variety of characteristics (such as speed, trafficking, and wavelength sensitivity) to allow for a greater variety of optogenetic manipulations. Some examples of this include finding solutions to increase the efficiency and efficacy of inhibitory opsins and the implementation of two-photon (2P) activated optogenetic tools; these two areas are the focus of this proposal. Ion-channel or Ion-pump opsins have been the most widely used for optogenetic inhibition, though they are restricted by off-target effects, poor performance at synaptic terminals, and require constant light to maintain their effect. Recently, there has been a shift in towards the development and use of GPCR-based opsins for inhibition, given they are more efficient synaptic terminal inhibition and have fewer off target effects. Opposed to ion-channel/pump direct hyperpolarization through the movement of Cl- or H+ ions, inhibitory GPCRs utilize Gi/o-protein effectors which lead to the activation G-Protein Coupled K+ channels (GIRKs) to hyperpolarize cells or inhibition of Voltage Gated Calcium Channels (VGCCs). The push to use GPCRs for optogenetic inhibition is recent, so there are just a few inhibitory GPCR opsins available. Lamprey parapinopsin, a reversibly activated inhibitory GPCR, is one example and the subject of this dissertation. To our knowledge, none of the GPCR-based inhibitory opsins have been characterized for 2P-use in neurons. 2P light has several advantages over single-photon excitation, allowing for greater depth penetration and excitation restrained to a single cellular-plane due to the lack of scattering. The off-target effects of ion channel inhibitory opsins along with the lack of GPCR-based opsin operational within multi-photon spectra excludes inhibitory optogenetics from many of the advantages of 2P microscopy, including multiplexing with other 2P sensitive tools. In this dissertation, we characterize LcPPO sensitivity to 2P-wavelengths by assessing LcPPO-GIRK coupling in a heterologous system and neurons. We then move on to understand how 2P-stimulated LcPPO (2P-LcPPO) affects somatic excitability in cultured neurons. The goal of this project is to demonstrate the potential LcPPO has for 2P optogenetic inhibition of neurons
Essays on Experimental Economics and Microeconomic Theory
No full textThis dissertation studies topics in experimental economics and microeconomic theory. In the first chapter, I study the relationship matching problem through theoretical analysis and lab experiments. In particular, I consider a two-stage matching model where agents can only divide a fraction of match surplus when forming a match, with the remaining subject to bargain within the match. I characterize stable matching outcomes under the assumption of the standard Nash bargaining solution within the match. Two special cases are Bargaining Before Match (BBM), where agents divide the entire surplus before forming a match, and Bargaining After Match (BAM), where the entire surplus is divided after a match is formed. While matching experiments in BAM produce more stable matches than in BBM, our experiments show the opposite in the non-extreme cases. I explain the experiment outcomes with the quantal response equilibrium. In the second chapter, I investigate when and why observing actions of others can either facilitate or hinder decision-making in a sequential social learning environment where all information is public. I conduct a laboratory experiment in which participants receive the same total information but differ in whether they observe others’ actions or raw signals first. Once a herd forms, seeing actions before signals significantly reduces the likelihood of making an optimal decision, and providing the signals afterward does little to remedy this effect. Analysis of time spent on signals and players’ reliance on herding actions suggests that initially seeing actions steers attention away from subsequently revealed signals, thus amplifying errors. In the third chapter, we study voters’ endogenous acquisition of costly signals in a setting where pivotality and state magnitude exert opposing effects on incentives. We consider a continuous state space, where signals and the stakes of the decision to vary with the underlying state. When the state has a large magnitude, signals tend to align, reducing the chance of an individual being pivotal but increasing the stakes of the decision. In contrast, states near zero generate conflicting signals, increasing pivotality while lowering the stakes. We show that when marginal costs of nearly irrelevant information are zero and exhibit diminishing returns in precision, the probability that the electorate selects the correct alternative converges to a state-dependent value strictly above one-half. If the marginal cost of acquiring initial information is nearly flat, the probability of a correct decision converges to one
Fields Under the Hoof: characterizing plant cultivation of agropastoralists in Bronze and Iron Age Inner Asia (3000 BCE - 1000 CE)
No full textThis dissertation examines the agropastoral practices in the Eurasian landmass between the 3rd millennium BCE to 1st millennium CE, focusing on characterizing how communities living in mountainous Inner Asia incorporated plant cultivation into their mobile agropastoralist lifestyle. I examine macrobotanical remains from key archaeological sites along the routes of the trans-Eurasian exchange of domesticated plants and animals and various technologies during the Bronze and Iron Ages. These sites include Chap, Kyrgyzstan, Tasbas, Kazakhstan, and Dingdong, Piyang, Jiweng, Kaerdong, and Bangga, located in Tibet. I use stable carbon and nitrogen isotope values of archaeological plant remains and macrobotanical assemblages to assess the labor (in the form of watering and manuring) dedicated to plant cultivation. Through this analysis, I investigate whether cultivation strategies travelled with the domesticated crops across the Inner Asian mountains or if these strategies were decoupled from the crops as they moved into new cultural and environmental settings. Findings indicate that communities developed localized crop management strategies, often taxa specific, rather than adopting a shared cultivation system. While these ancient communities shared similar crop – and livestock – compositions, they adapted and modified cultivation practices for each of their locales. This research provides insights into the broader implications of agricultural intensification on paleodietary reconstructions, the role of dynamic pastoral systems in shaping agricultural practices, and the localization of agropastoral strategies across Inner Asia. The results show the remarkable flexibility of agropastoralists living at high elevations who incorporated both mobile livestock husbandry and plant cultivation to succeed in sometimes fairly hostile environments for agricultural pursuits. Future research avenues are outlined to further explore the interplay between domesticated plants and animals and their cultural contexts. This work contributes to the understanding of how ancient agropastoral communities navigated the complexities of integrating new agricultural technologies and domesticated species, ultimately transforming both their local environments and the broader Eurasian agrarian and agropastoral history
Bayesian Uncertainties: A Post-Modern Development in Nuclear Interactions
No full textOver two decades ago, nuclear physicists met in Trento, Italy, to discuss the then-modern developments in low-energy effective field theories (EFTs) of quantum chromodynamics to describe the interactions between nucleons, making so-called microscopic EFT nuclear interactions. In the summer of 2024, they reconvened after 25 years to discuss the current, post-modern status of nuclear interactions, which have become prolific in nuclear physics since the first meeting. One of the discussion points as a post-modern development was the introduction of Bayesian methods to EFT nuclear interactions. This thesis explores the developments in Bayesian methodologies for ab initio nuclear physics, focusing primarily on uncertainty quantification and model calibration. We demonstrate the usefulness of a Bayesian framework in EFT interactions with the inclusion of uncertainty during model calibration, allowing us to extract meaningful physics from data. Further, we examine the ramifications of power-counting EFT potentials and the implementation of new, widespread computational methods, which can allow for the consistent propagation of uncertainties to all nuclear calculations
It’s Not Too Late for States Parties to Fulfill the Promise of the International Criminal Court: Three Actions They Should Take Now
Get PDFWhat to do about a world in which atrocity crimes appear to be occurring with increasing and alarming frequency? Wars are prosecuted using scorched earth tactics that involve the commission of war crimes and crimes against humanity, credible allegations of genocide have been leveled at States in several corners of the globe, and acts and wars of aggression, which will be the subject of discussion at the upcoming International Criminal Court (ICC) Review in July, are on the rise.
The United Nations and other international institutions seem powerless to prevent or contain the violence, and the ICC, which was created in 1998, seems increasingly to be a “Potemkin Tribunal”: the majority of the Court’s arrest warrants have not been implemented (with the notable exception of the former president of the Philippines, Rodrigo Duterte), the Prosecutor is on leave due to serious allegations of sexual misconduct, and the courtrooms show few signs of activity.
How did this happen? Observers cite many reasons. But the ICC might still play a role in walking humanity back from the brink, if States can find the political will to respect and strengthen the work of the Court. ICC States Parties could take three concrete actions to address the current downward spiral: (1) support the arrest of defendants wanted by the ICC and uphold the unanimous ICC Appeals Chamber ruling that there is no immunity for heads of State, (2) amend the Rome Statute to remove the jurisdictional limits imposed upon the crime of aggression during the Kampala Review Conference in 2010, and (3) continue to uphold the values of the Court and the integrity of its activities, while encouraging other States to ratify the Rome Statute to enhance the ICC’s legitimacy and universality
When Threat and Safety Cues are Present: A Quantitative Study Exploring the Relationships Between Childhood Adversity, Social Support Figures, Subjective Safety, and Child Well-Being Outcomes
No full textChildhood adversity has become a global social concern because its potential traumatic effects may lead to longer-term adverse health, psychological, and social outcomes for children, their families, communities, and society (Bellis et al., 2019; Hughes et al., 2021; Kim & Royle, 2024). Safety has long been proposed as a central element in treating trauma, promoting recovery of traumatic stress-related disorders (e.g., post-traumatic stress disorders (PTSD), depression, anxiety) and psychological well-being (Bloom & Farragher, 2013; Herman, 1992; Hobfoll et al., 2007; Porges, 2021; van der Kolk, 2003). Scant work, however, has focused on the impacts of adversity on children’s safety perception, such as feeling (un)safe in the absence of an active threat following an adverse experience compared to adults (e.g., Basile et al., 2022). Social support is noted as a protective factor in relation to reactions to child trauma, but it is not known if this may improve outcomes due to an association with helping children feel safe. Further, little is known about whether perceived safety may buffer the effects of adversity on childhood mental health and well-being. This dissertation aims to help address some of the gaps in our understanding of how childhood adversity, safety perception, and social support may impact later child well-being outcomes. Based on a proposed conceptual model of safety in the context of childhood adversity, multinomial logistic regression and ordinary least squares regression were used to conduct secondary data analysis with two publicly available datasets: the Future of Families and Child Wellbeing Study (FFCWS) and Children’s Worlds: International Survey of Children’s Well-Being (ISCWeB). Three specific aims examined aspects of the relationships between these constructs. Overall findings indicate an interconnected picture: childhood adversity and/or material hardship influence children’s safety perception as well as their mental and psychological well-being. Although the two data sets measured the constructs in somewhat different ways both saw direct effects on perceived safety at school and in the community. While only the global dataset addressed perceived safety at home, there was a similar pattern. The results did not support a moderating effect of perceived safety in associations between children’s experiences of adversity or poverty and depressive and anxiety symptoms (FFCWS) or psychological well-being (ISCWeB). There was a moderating effect of the presence of social support figures, however, found in the ISCWeB data. Specifically, social support figures exhibited a stronger positive association with psychological well-being for those children who reported feeling less safe at home, school, and in the community. These findings align with theoretical perspectives emphasizing the significance of safety in mental health, trauma recovery, and child development (Herman, 1992; Moore & Lippman, 2005; Porges, 2021; van der Kolk, 2014) and add to the scant empirical findings related to the potential interconnected relationships between childhood adversity, safety, and child well-being. This dissertation suggests that restoring the perceived safety of children exposed to adversity, as well as assuring children have positive social support figures in their lives, may be a promising way to intervene in childhood adversity and modify its negative consequences