Leveraging Rehabilitation and Implantable Strain Sensors to Improve Bone Healing After Traumatic Femur Fractures

The primary objective of this thesis was to quantify patient-specific loading and rehabilitation parameters to elucidate how specific rehabilitation conditions impact bone healing after traumatic bone injuries. Our overall hypothesis was that parameters of mechanical loading and exercise will impact bone healing. To test this hypothesis, we utilized three rehabilitation platforms that enabled investigation of distinct rehabilitation parameters. These platforms including (1) a rodent running wheel with engineered resistance brakes or on/off brakes to enable running of different intensities or durations, respectively, (2) a treadwheel with an adapted on/off brake as a scalable platform, and (3) altered treadmill with speeds conducive to rodent needs. These platforms allowed for the investigate of distinct rehabilitation platforms and their relationship to bone healing. We also used implantable wireless strain sensors that enabled real-time non-invasive monitoring of mechanical cues as a function of time, rehabilitation conditions, and healing status. In collaboration with University of Utah, we used these sensors and in vivo microCT scans to develop subject-specific finite element models to quantify niche mechanical cues during different rehabilitation conditions. We discovered that higher intensity rehabilitation, relative to rehabilitation of lower intensity, increased early-stage strain magnitudes and significantly improved bone healing, with explant femurs matching intact strength. Beyond loading magnitude, we also discovered the importance of both long term and short term on bone healing. Nonlinear multivariate analyses revealed that rehabilitation must balance activity and rest to improve bone healing, where rehabilitation with longer running distance and shorter daily rest periods resulted in 100% union after 3 mm bone injuries. These results further found that the necessary balance of rehabilitation and rest depends on subject-specific factors such as injury size since the same rehabilitation conditions resulted in only 20% union after a 2 mm bone injury but 100% nonunion after a 3 mm bone injury. Using previous studies to inform a rehabilitation regimen predicted to improve bone healing, we also found the importance of short-term rest between exercise loading bouts. Rehabilitation that involved steady-state running for 12 minutes significantly hindered bridging and bone formation compared to rehabilitation that involved intermittent rest periods between one minute running bouts. Systemic myeloid-derived cell types, previously predicted to impair bone healing, were also downregulated for rehabilitation with short-term rest periods. These results highlight rehabilitation with data-informed levels of intensity, activity, and both short and long term rest as a therapeutic to modulate early mechanical loading and the immune response to enhance bone repair.This work facilitated a deeper understanding of how specific rehabilitation parameters regulate mechanical cues and bone repair and validated an implantable sensor platform to further investigate mechanobiology. This thesis aids in the development of subject-specific rehabilitation with the novel insight into the importance of rest on bone healing. Our results challenge the fields focus on optimizing the loading magnitude to improve bone repair. In addition, this thesis provides foundational support for the commercialization of implantable sensor technologies to track implant mechanics as a noninvasive feedback of healing status and to inform personalized clinical decisions. This dissertation includes content from several published articles including Nash* et al. (2022) Connective Tissue Research; Nash* et al. (2022) Physiology in Health and Disease, Springer; Williams and Harrer et al. (2024) NPJ Regenerative Medicine; and Williams et al. (submitted 2024) Science Advances. *Publication under maiden name: Kylie Nas

Disruption of Ribosome Biogenesis and Induction of Nucleolar Stress by Platinum(II)-based Chemotherapeutics

Platinum(II) metal complexes—cisplatin, carboplatin, and oxaliplatin—represent a major class of antineoplastics agents used in a majority of cancer treatment regimens throughout the world. Despite their ubiquitous use, the precise mechanisms and targets responsible for cancer cell death are not fully understood. Overcoming these deficiencies will be necessary to address the limitation associated with current Pt-based chemotherapeutics in the clinical setting. Current literature has revealed, unlike cisplatin and carboplatin, oxaliplatin primarily kills cells through disruption of ribosome biogenesis. Ribosome biogenesis is intimately connected to the nucleolus, a phase-separated nuclear condensate, which also functions as a central hub for sensing and coordinating cellular stress response through nucleolar stress response.This work provides insight on the relationship between Pt(II) compounds and disruptions in ribosome biogenesis, and the impact on nucleolar structure. Chapter I summarizes the significance and current understanding of Pt-based chemotherapeutics in the context of ribosome biogenesis and the nucleolus. Chapter II identifies structural and chemical properties of Pt(II) compounds necessary for nucleolar stress induction through a novel immunofluorescence imaging approach for quantifying nucleolar stress. Chapter III applies this framework to a subset of monofunctional Pt(II) compounds which are also shown to induce nucleolar stress. Chapter IV examines spatiotemporal differences in nucleolar stress induced by Pt(II) compounds identified in previous studies—ruling out connections with intracellular accumulation and DNA binding. Chapter V discusses current progress on elucidating the molecular mechanisms for inhibition of rRNA synthesis by oxaliplatin by adapting a ChIP-based sequencing techniques to map the occupancy of RNA Polymerase I machinery along rDNA. Chapter VI provides a comprehensive review on the coordination metal ions with nucleic acids, highlighting recent examples of NMR and x-ray crystallography structures from the literature. This dissertation includes published and unpublished co-authored material

Improving Earthquake Rapid Response and Early Warning Performance with Geodesy and Machine Learning

This dissertation focuses on the work I have undertaken to investigate how quickly and accurately we can characterize earthquakes while and immediately after they occur, and potential ways to improve the systems we use for this. I focus on how we can use the modern technology we have for Earth monitoring as well as modern data processing and analysis techniques such as machine learning to improve the capabilities of the systems we rely on for earthquake disaster response. In this dissertation I present an exploration into the question of how early earthquakes are distinguishable by magnitude using borehole strainmeters, where we found that earthquakes do not appear to be strongly deterministic (i.e., large earthquakes are not inherently different from small earthquakes in their beginning stages). This has implications for how long it takes to accurately determine the magnitude of an earthquake, particularly for large events which rupture over longer periods of time. I then discuss our development of a machine learning algorithm for improving the performance of earthquake early warning systems for large earthquakes. This algorithm allows for discrimination between noisy GNSS waveforms which do actually contain seismic waves from earthquakes and those which do not, which enables us to reduce the amount of high-noise/low quality data that enters algorithms which determine the magnitude of such earthquakes. While earthquake early warning systems tend to operate only over specific regions such as the U.S. West Coast, organizations such as the USGS’s National Earthquake Information Center also must rapidly publish information such as magnitude about worldwide earthquakes to aid in response efforts. However, magnitude estimation across a large range of earthquake sizes and tectonic settings is technically difficult. To help streamline this process, we developed another machine learning model which allows for the estimation of earthquake magnitudes uniformly for all locations and tectonic settings worldwide, which is also presented in this dissertation. Six multi-frame animations with more figures from this chapter are included as supplemental video files. This dissertation includes previously published and unpublished co-authored material

The Influence of Positive Maternal Involvement on the Relationship Between Maternal Emotion Dysregulation and Preschooler Internalizing and Externalizing Problems

Children of mothers with elevated emotion dysregulation (ED) may be at greater risk for developing internalizing (INT) and externalizing (EXT) problems and, in turn, future psychopathology. While previous studies have investigated early risk pathways that may explain this association (e.g., unsupportive maternal responding), our understanding of factors that protect against the downstream effects of maternal ED on child outcomes is limited. To explore prospective protective factors, the current study examined the moderating role of positive maternal involvement on the relationship between maternal ED and preschoolers’ INT and EXT problems. This study included 178 mother-child dyads, where maternal ED was assessed using the Difficulties in Emotion Regulation Scale, positive maternal involvement was assessed using the Alabama Parenting Questionnaire – Preschool Revision, and preschoolers’ INT and EXT problems were assessed with the Child Behavior Checklist. Maternal ED and positive maternal involvement had significant direct effects on preschoolers’ INT and EXT problems; however, the moderating effect of positive maternal involvement on the relationship between maternal ED and preschooler INT and EXT problems was nonsignificant. Further examination of factors that may mitigate risk among children of mothers with elevated ED is necessary to inform effective prevention and intervention efforts

The Roles of Processing Difficulty and Numeracy in the Use of Numeric Risk Information

One of the key challenges in risk communication is effectively conveying numeric information to the public. Research suggests that numeric information is often more complex and less likely to be used than narrative information, such as individual stories. This may be because numbers are more cognitively demanding, leading decision-makers to rely on easier-to-use narrative content. However, a study on the representativeness heuristic (judging probabilities based on resemblance) found that the use of information depends not on its type but on its difficulty and the cognitive resources available. Specifically, when cognitive resources are limited, people are more likely to use numeric information that is easier to process (shorter and presented before a long narrative) than they are to use more complex numeric information (longer and presented after a short narrative). However, when resources are ample, they are more likely to use more complex numeric information (longer and presented after a short narrative) than they are to use numeric information that is easier to process (shorter and presented before a long narrative). The present two studies extended these ideas into risk assessment, focusing on numeracy instead of cognitive resources. It was hypothesized that participants paradoxically would be more sensitive to risk levels when numeric information was harder to process, with this effect being stronger among highly numerate individuals. In Study 1, the difficulty of information was manipulated by varying its length and order of presentation; in Study 2, it was manipulated by varying numeric precision and order of presentation. Results from Study 1 supported the hypothesis that participants would be more sensitive to risk levels when numeric information was harder to process (longer and presented after a short narrative) compared to when it was easier to process (shorter and presented before a long narrative). Interestingly, number preferences, rather than numeracy, emerged as a significant moderator in Study 1. However, the manipulation in Study 2 was unsuccessful, and the anticipated effects were not observed. Implications for enhancing risk communication strategies were subsequently discussed

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Hello Neighbors! Investigations of Housing and Social Cohesion of Afghan Refugees in the United States

Resettlement gives refugees a chance to restart and gain a normal life in a foreign land. For Afghan refugees, however, their unfamiliarity to American culture and norms, negative media portrayal, or perceived competition for limited resources may cause them to be socially isolated and bring about perceptions of otherness among neighbors. This may result in lowering neighborhood efficacy or community cohesion. While social cohesion has been gaining more ground in academic migration research in the last decade, limited research has paid attention to resettlement countries. To date, there is no published study on social cohesion in U.S. refugee-receiving cities. This leaves an underexplored gap of understanding regarding the spatial impact on social life and social cohesion in U.S. resettlement communities. In this examination, I employ a mixed-method approach including document analysis, interviews, surveys, and observations. I present two case studies: Sacramento, CA and Eugene, OR focusing on the housing experiences and social life of Afghan refugees. The framework is built upon theories of social cohesion in conjunction with refugee integration and the built environment. The investigation is centered around space and spatial qualities that promote social interactions and the relationships among community members. This study seeks to determine how refugees make their presence in everyday residential and public spaces. The findings suggest that 1) a sense of belonging, privacy and control, and perceived crowding are key attributes of living places that promote both intergroup and intragroup interactions on daily basis; and 2) increased freedom of mobility has resulted in a dispersed residential pattern which positively associates with improved spatial integration. Ultimately, this study provides data-driven suggestions on housing and socio-spatial transformations for a refugee-receiving city

The genomic outcomes of recent and ancient hybridization across a monkeyflower radiation

New species can form when populations diverge without the homogenizing effects of gene flow. In these cases, genetic and phenotypic differences are able to accumulate, leading to the evolution of reproductive isolation. However, recent genomic analyses have shown that speciation can proceed even with frequent hybridization. This is often due to the effects of natural selection acting against alleles at loci that lead to reduced hybrid fitness. Prior to the evolution of reproductive isolation, hybridization can occur throughout the history of diverging lineages, sometimes facilitating the transfer of beneficial alleles. Thus, by investigating the mechanisms that influence gene flow among hybridizing taxa at various stages of divergence, we can better understand how speciation occurs despite gene flow. In this thesis, I explore the genomic outcomes of hybridization among taxa in the Mimulus aurantiacus species complex, a diverse radiation of wildflowers exhibiting extensive floral and ecological diversity. Leveraging this diversity, I conducted multiple tests for admixture to reconstruct the history of hybridization within this complex. In Chapter 2, I show that ancient hybridization has led to the recurrent evolution of red flowers within the most diverse clade of this radiation. In at least one instance, this ancient hybridization led to strong selection favoring red flowers, which has contributed to the evolution of reproductive isolation. Chapter 3 examines the history of introgression between two hybridizing taxa endemic to the Channel Islands of California, revealing evidence for both recent and ancient hybridization, with stronger selection against recent introgression. Chapter 4 investigates a contemporary hybrid zone between two recently diverged taxa in southern California, finding that selection against gene flow at barrier loci contributes to their differentiation. Collectively, these findings demonstrate how hybridization occurring at different points in time can result in divergence that can fuel diversification or can lead to the maintenance of species barriers

Journal Editorial: “Research as Learning and Being”

Dr. Ahmar Zaman received his PhD in clinical psychology from the University of Detroit Mercy in 2020. He completed his predoctoral internship in 2020 at Harris County Juvenile Probation with the Forensic Department in Houston, Texas. He completed his postdoctoral fellowship in adolescent forensic and addiction psychology through the Warren Alpert Medical School of Brown University in 2021. Dr. Zaman’s clinical interests include conducting forensic psychological evaluations with adolescents involved with the juvenile justice system and working with youth in areas related to racial, cultural identity, and intersectionality. His research interests explore understanding how mental health, socioeconomic status, and racial and gender identity impact youth becoming justice-involved. In his free time, he enjoys road trips, photography, volleyball, and milkshakes.Every developing child is learning to understand the world and their place in it. They do this through touching, experimenting, questioning, and watching the world around them; every question they have is their own research question to make sense of their world