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UC San Diego Electronic Theses and Dissertations

The Vitamin D Metabolite Ratio and Incident Cardiovascular Disease: The Multi-Ethnic Study of Atherosclerosis

(2024)

Investigations into the link between vitamin D and cardiovascular disease (CVD) have yielded inconsistent results. The vitamin D metabolite ratio (VMR), the ratio of 24,25(OH)2D to 25(OH)D, has shown stronger associations with fracture and mortality than 25(OH)D alone. Our study assessed the association between the VMR and CVD outcomes. We evaluated a cohort of 6,313 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), without pre-existing CVD, over 15 years. Utilizing Cox regression, we examined the associations of both the VMR and 25-hydroxyvitamin D [25(OH)D] with various cardiovascular events. Over the study, 800 participants developed CVD, including conditions such as myocardial infarction, resuscitated cardiac arrest, stroke, coronary heart disease death, and stroke death. Heart failure (HF) was observed in 398 participants, and 413 experienced cardiovascular mortality. Models were adjusted for factors including demographics, lifestyle, clinical conditions and medications, biomarkers, and kidney function. Participants averaged 62 years (range 44-84), with 53% females. The mean (SD) 25(OH)D level was 22.7 (11.0) ng/mL, and the mean VMR was 15.2 (5.0). In fully adjusted models, a two-fold increase in VMR was associated with a 24% reduction in incident CVD (HR: 0.76, 95% CI: 0.65-0.88). However, there was no association between the VMR and HF (0.98, 0.78-1.24), or cardiovascular mortality (0.96, 0.77-1.21). 25(OH)D was not significantly associated with any CVD outcome. In a diverse cohort, VMR was significantly associated with reduced incident CVD, but not HF or cardiovascular mortality. The results suggest that VMR may provide greater insight into vitamin D metabolism, compared with 25(OH)D alone.

Measurement Error and Causal Inference: Implications in the analysis of mobile-health data

(2023)

Wearable devices have been gaining popularity in biomedical studies and clinical trials. In recent years, wearable devices have become more common in the study design stage and for data collection purposes. Wearable devices, such as accelerometers and Fitbit, have not only made collecting data for participants much easier than before but also can capture subjects' activities along with other important biometrics more objectively than surveys and other traditional data-collecting methods. However, despite the potential benefit of using those technology-based trackers to collect data and potentially boost wearers' activity levels, very little is known about how individuals use these trackers on a daily basis or how tracker use relates to increasing physical activity or changing sedentary behaviors. Additional research is needed to understand how best to utilize trackers in interventions to support self-monitoring and effectively change behaviors. Furthermore, statistical methods for correcting estimates from activity measures that contained measurement error, and investigating causal inference between lifestyle interventions and activity level have not been fully exploited. There is a need for novel statistical approaches to answer the above questions in both randomized control trials and observational studies.

The goal of this dissertation is to develop appropriate and innovative statistical methods to answer the questions fore-mentioned, while trying to close the gap between available dense continuous mobile health data and appropriate statistical methods.

The dissertation consists of three main chapters. In chapter one, we used minute-level activity data collected from Fitbit trackers in a randomized controlled trial of breast cancer survivors to examine physical activity levels and adherence to Fitbit use. We examined patterns of activity level and Fitbit use for both the 12-week intervention period and the 2-year follow-up period and compared patterns between the intervention group and the control group. We found that within the first 3-month intervention period, the Exercise group has a higher average of MVPA and adherence to Fitbit use than the Wellness group, but the trend of MVPA and adherence to Fitbit use are no differences between the two groups. Besides that, both the Exercise and Wellness group showed a dropping trend of MVPA and adherence to Fitbit use in the follow-up period, but the Exercise group has a much slower dropping trend than the Wellness group.

Realizing the amount of measurement errors and extreme values contained in the activity data captured by those wearable devices in chapter one, and motivated by the existence of measurement errors in sedentary behavior assessment arising from different sources poses serious challenges for conducting statistical analysis and obtaining unbiased estimates, especially without validation data \cite{aim2_2}, in chapter two, we proposed to use structure models consisting of Linear Mixed Effect Models and Generalized Linear Models to obtain unbiased estimates of the relationship between exposures subject to measurement errors and outcome of interest, after appropriately accounting for the errors in devices' measurement. In the motivating example of chapter two, we found that without accounting for errors in the measurements, we may end up inappropriately exaggerating the effect of sedentary time on subjects' BMI and disseminating invalid health guidance to the population.

To investigate causal inference between lifestyle interventions and activity level while addressing the extreme values of the measurements from the wearable devices, in chapter three, we proposed a double robust estimator to extend the traditional Mann Whitney Wilcoxon Rank Sum Test (MWWRST) for causal inference in observational studies. The proposed estimator not only addresses the limitations of existing alternatives for more robust and reliable inference when applying the MWWRST to observational study data, but also performs well for small sample sizes. Meanwhile, The results from the real weight-loss trial showed that in addition to the doubly robust properties, the proposed estimator also effectively addressed outliers and extreme values.

Cover page of A Framework for Generalized Steady State Neural Fluid Simulations

A Framework for Generalized Steady State Neural Fluid Simulations

(2023)

Steady State fluid simulations are a critical piece of the mechanical engineering design loop but serve as a bottleneck due to the engineering overhead and the high computational load. In recent years, there has been an increase in the research activity in the field of neural fluid simulations, however, the current works have limited scope with respect to the fluid domains and flow regimes, restricting their generalizability and their potential industrial impact. This thesis seeks to introduce a foundational framework for generic 3D steady state neural fluid simulations, with the goal of simplifying and expediting the fluid simulation process for engineering applications. To that end, this project introduces 3 key contributions: A python package for generating and post-processing fluid simulations in Ansys in an automated end-to-end fashion, a benchmark dataset of over 3060 fluid channel geometries and roughly 3400 quality fluid simulations in line with engineering standards for accuracy, and a series of foundational experiments exploring steady state neural fluid simulations for internal channel flows - the first of its kind as far as the author is aware. Experimental results demonstrate that geometric deep learning models have the capacity to be used as a proxy for traditional fluid simulations, but also indicate that further research is required to continue to develop the datasets and architectures for this deep learning application.

Cover page of Principals’ Leadership Practices: A Qualitative Study to Understand Principals’ Use of Human-Centered Leadership as a Response to COVID-19

Principals’ Leadership Practices: A Qualitative Study to Understand Principals’ Use of Human-Centered Leadership as a Response to COVID-19

(2023)

Little is documented in the literature about the leadership practices of principals during times of crisis. This study used semi-structured interviews and document collection methods to broaden understandings of principals' decision-making during the COVID-19 pandemic. Specifically, the study aims to highlight the novel challenges faced by principals during the pandemic, how they responded to these challenges, and who and what they prioritized as they made decisions. The findings suggest that these principals experienced instructional, student, and communication challenges between March 2020 through June 2022. This study highlights the way these principals engaged in human-centered leadership which considers the needs of the people in the school system while also ensuring goals and tasks are completed. This has implications for policy and social justice where school administrators must exercise leadership beyond the instructional and highlights how actions can positively impact equity and access to curriculum for marginalized students.

Cover page of Time-dependent response of lithosphere to earthquakes: Case studies in Tibet and California

Time-dependent response of lithosphere to earthquakes: Case studies in Tibet and California

(2023)

In this dissertation, I use Interferometric Synthetic Aperture Radar (InSAR) and Global Navigation Satellite System (GNSS) to study time-dependent crustal deformation due to several recent large earthquakes (M > 7) at the margin of Tibetan Plateau and in the eastern California shear zone (ECSZ), in order to have a better understanding of earthquake triggering process, lithospheric rheological and frictional properties during the earthquake cycle. Chapter 1 is an introduction to the tectonic background and the data I used in each following chapter. Chapter 2 studies surface displacements due to the 2019 Ridgecrest earthquake sequences, and investigates stress transfer and possible triggering relationships between pre-mainshock seismicity and the M7.1 mainshock. Because historical studies reveal different lithospheric rheologies across different margins of Tibetan Plateau, chapter 3 focuses on the study of 5-year postseismic deformation following the 2015 M7.2 Sarez (Pamir) earthquake to place the constraint on the viscosity of the lower crust beneath the west margin of Tibet Plateau. Chapters 4 and 5, by contrast, aim at constraining the viscosity of the lower crust beneath the north-east margin of Tibet Plateau. Consistent with previous postseismic studies of Tibetan earthquakes, we did not find any evidence of a low viscosity channel (10^{16} ∼ 10^{17} Pa s) beneath Tibetan Plateau margins. Moreover, studies of M > 7 strike-slip earthquakes that occurred in Tibet and California all suggest ∼ 30% of coseismic shallow slip deficit compared to its peak slip occurred in the depth interval of 3 − 4 km. The deficit is insufficiently accommodated by both interseismic and postseismic slip, which indicates off-fault yielding over multiple earthquake cycles. Chapter 6 proposes an inversion optimization method that aims to use the least number of parameters to fit geodetic observations almost equivalent well. We designed an 1D inverse problem that used synthetic surface data to invert slip distribution beneath the surface. The method we proposed reduces more than 2/3 of unnecessary number of parameters but achieves a good fit required by a certain uncertainty threshold.

Biophysical investigation of protein liquid-to-solid phase transitions and their modulation by small heat shock proteins

(2023)

Many of the proteins found in the pathological protein fibrils and aggregates that are associated with neurodegenerative disease also exhibit tendencies for liquid-liquid phase separation (LLPS) both in vitro and in cells. The transition between the LLPS state and the aggregate state can be modulated by protein chaperones that can block the liquid-to-solid transition and help maintain the LLPS state. In this dissertation, we characterize structural features exhibited by FUS LC, a protein that has been demonstrated to facilitate LLPS and form fibrils, as it undergoes a liquid-to-solid transition from the LLPS state to the fibril state. We subsequently examine the α-crystallin chaperone HSPB1 as it interacts with FUS LC in the LLPS state, and compare the structural features of HSPB1 without a client protein to its structural features in the presence of a phase-separated and an aggregated client protein. The heterogeneous nature of the chaperone and client system and the wide range of dynamics adopted by the component proteins present unique challenges for structural interrogation. We therefore integrate solid-state magic angle spinning NMR spectroscopy, coarse-grained molecular dynamics simulations, and cryo-EM to build a model for the structures and dynamics adopted by FUS LC during the liquid-to-solid transition and HSPB1 as it interacts with client proteins, with a specific focus on the role of the N-terminal domain of HSPB1 in client recognition and chaperone function.

Nanomedicines for Transient Ultrasound Imaging and Cancer Immunotherapy

(2023)

Advancements in nanomedicines have enabled breakthroughs in both disease diagnosis and treatment, including ultrasound bioimaging and cancer immunotherapy. On the one hand, nanomedicines of various formulations have been used as ultrasound contrast and greatly improved the ultrasound imaging quality. However, an ideal ultrasound contrast agent— that has tunable, modifiable surface, biodegradability, biocompatibility, and sufficient stability (half-life) for transient ultrasound imaging— is yet to be explored. On the other hand, to overcome the limitations of immune checkpoint blockage therapy,— immune-related toxicity and inefficacy in immune-suppressive tumors— nanomedicines have been rationally designed to trigger immunogenic cell death (ICD) of tumor cells. However, further work is necessary to develop ICD-inducing nanomedicines that are biodegradable, biocompatible, and intrinsically potent in inducing ICD. In this dissertation, I will discuss how creating novel nanomedicines can benefit both ultrasound imaging and cancer immunotherapy.First chapter reviews applications of nanomedicines in both ultrasound imaging and ICD-based cancer immunotherapy, with a highlight of successes and limitations of existing nanomedicines. Second chapter describes how sol-gel reaction combined with electrospray can generate biodegradable calcium phosphate micro/nano particles. Effects of synthetic parameters on the particle size and morphology are discussed in detail. The biodegradability of these particles was validated. Third chapter illustrates a bio-inspired, facile, mild, and solution-based synthetic method for creating calcium phosphate micro/nano particles. Systematic investigations on synthetic parameters led to calcium phosphate particles with versatile sizes (396±128 nm to 63±8 µm) and morphologies (hexagonal micro-disc, micro-flower, micro-leaf, nano-butterfly, and nano-ribbon). A “phosphate sponge” mechanism was found to be the key for regulating the particle sizes and morphologies. These calcium phosphate micro/nano particles are proven to be biodegradable, non-toxic, and efficient in creating transient ultrasound contrast. Fourth chapter studies the building of proton sponge nano-assembly (PSNA) optimized for imaging and triggering ICD of cancer cells. By carefully tuning the hydrophilic and hydrophobic components, the self-assembly tendency of PSNA was optimized. In turn, the PSNA with the highest fluorescence, positive surface charge density, intracellular fluorescence, and cancer cell cytotoxicity was achieved. The lysosome rupturing-regulated pyroptosis and necroptosis were triggered by PSNA, suggesting the great potential of the PSNA for anticancer immunity.

Evidence for ZIC1 as a Novel Gene in Idiopathic Hypogonadotropic Hypogonadism

(2023)

Idiopathic Hypogonadotropic Hypogonadism (IHH) is a genetic disorder that can lead to delayed or absent puberty, poor development of secondary sex characteristics, and infertility. This occurs because of reduced levels of Gonadotropin-Releasing Hormone (GnRH) in the Hypothalamic-Pituitary-Gonadal (HPG) axis. Surprisingly, more than 50% of patients do not know the specific mutation causing their disorder. Our collaborators conducted whole exome sequencing in IHH patients without known genetic causes for their disease. They were able to identify novel, deleterious mutations in ZIC1, a transcription factor in the cerebellum, in multiple families in the cohort. The heterozygous mutations presented here are from four unrelated families: H134Rfs*21, Y286X, E299K, and S413Y. Unfortunately, there is no current research on ZIC1 in the reproductive pathway. My goal is to identify evidence linking ZIC1 and IHH by understanding its molecular mechanisms in the reproductive pathways. First, I transfected a shRNA to knockdown endogenous ZIC1 and observed that GnRH-Luciferase expression decreased in the GT1-7 cell line. I observed that transfection in the GT1-7 cell line of three ZIC1 mutated plasmids reversed the ZIC1-mediated expression of GnRH-Luciferase, while in the GN11 cell line, two mutations induced GnRH-Luciferase. My study will allow identification of ZIC1 as a novel regulator of the HPG axis and a potential cause for IHH.

Strain-specific Genetic Mutations in Melanin Production Pathway Affects Cortical Alpha-synuclein Expression in A Mouse Model of Parkinson’s Disease

(2023)

Parkinson’s disease (PD) is characterized by the extensive loss of nigrostriatal dopaminergic neurons, leading to the substantial motor deficits which is usually served as a major diagnostic symptom. Recent studies have shown that alpha-synuclein (Syn-1) over-expresses in the brains of patients with PD, and Masliah lab in UCSD has developed a mouse model to study the Syn-1 expression. This mouse model is called Line 61, which accumulates wild-type human Syn-1 under the Thy-1 promoter. Here, we have further categorized the Line 61 mice by their coat colors (black and grey) in order to standardize this mouse group and highlight the importance of mouse selection in research using multi-color mouse models. We found that grey mice had significantly shorter latency to fall in the rotarod test and significant more Syn-1 and pSyn in CA1 than black mice, suggesting that future research doing behavioral tests with multi-color mice should consider the effect of coat color and limit to the mice with only one coat color.

A Study in the Design for Automated Human Brain Organoid Culture

(2023)

With the increasing global interest in space exploration and the permanent presence ofhumans in Low Earth Orbit (LEO), it is crucial to establish the impact of microgravity exposure on the human body, and specially, the central nervous system (CNS). In collaboration with Space Tango, the Muotri Lab is targeting the microgravity environment by sending cortical brain organoids for 30 day missions to the International Space Station. Brain organoids are tridimensional self-organized structures derived from induced pluripotent or embryonic stem cells that mimic the cellular diversity and the spatial architecture of the developing human brain. We foresee that studies using organoid models on Earth versus LEO will improve our understanding of brain biology and cell-to-cell interactions. This will allow us to assess the impact of the space environment on the human brain and ultimately alleviate the effects of long-term exposure to space in humans. This project requires designing an automated device (CubeLab) capable of replicating organoid culture on board of the ISS. Here, we perform several ground control experiments to define the baseline conditions of organoid growth and survival in order to simplify and improve the design of our CubeLab.