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The role of multivitamins: an investigation into the association with colorectal cancer survival
No full textThesis (Master's)--University of Washington, 2023Background: Nutritional supplements are used by over half of United States adults, and many patients use supplements for their perceived anti-cancer benefit. Current evidence for the relationship between multivitamin use and colorectal cancer (CRC) survival is sparse. Some studies suggest that multivitamins may divert attention from healthful food-based diets or multivitamin use may be reflected in an effort to live a healthier lifestyle consequently impacting CRC survival. In this study, we examined the association of pre-diagnostic multivitamin use with CRC survival, while accounting for differences by fruit and vegetable consumption and smoking status. Methods: This study uses data from two large prospective patient cohorts; the Colon Cancer Family Registry (C-CFR) and the Advanced Colorectal Cancer of Serrated Subtype (ACCESS) study. A Cox Proportional Hazards regression was used to assess the relationship between pre-diagnostic multivitamin use and CRC-specific survival (reported as hazard ratios (HR) and 95% confidence intervals (CI)). We also examined effect modification by fruit and vegetable consumption and smoking status.
Results: The estimated HR of CRC death for individuals who use multivitamins is 1.05 (95% CI: 0.94-1.18, p=0.4) compared to individuals who do not use multivitamins, suggesting no statistically significant evidence of an association between pre-diagnostic multivitamin use and CRC-specific survival. Users of multivitamins were less likely to have a history of smoking and consumed higher levels of fruits and vegetables; however, there was no evidence of effect modification by these variables in the relationship of multivitamin use with CRC survival.
Conclusion: We found no evidence of an association between pre-diagnostic multivitamin use and CRC survival, regardless of stratification by smoking status and fruit and vegetable consumption. Clinicians should discuss a variety of approaches for healthful activities individualized to the patient post CRC diagnosis in addition to multivitamin use advice
Advancing Hydrogen Deuterium Exchange Mass Spectrometry Through the development of Novel Internal Exchange Reporters
No full textThesis (Ph.D.)--University of Washington, 2023Hydrogen deuterium exchange mass spectrometry (HDX-MS) is a powerful tool for protein structure analysis. The remarkable versatility and sensitivity of HDX-MS renders the technique uniquely well suited to probing challenging biological systems. Over the last two decades advancements in mass spectrometers, sample handling techniques, and software tools have brought HDX-MS into the mainstream by dramatically improving data quality. Despite this renaissance, HDX-MS measurements remain very challenging to reproduce. The strong solution dependence of the chemical process underlying amide HDX contributes significantly to irreproducibility; even small variations in temperature or pH can have a pronounced effect on the deuterium uptake by a protein. As a result, a myriad of controls have been developed to help the investigator identify and address variations in solution conditions. Among these controls are compounds which directly monitor the conditions under which amide exchange takes place. These compounds, referred to as internal exchange reporters (IERs), have been the focus of my graduate work in the Guttman Lab at the University of Washington. When my work in the area began, the concept of reporting controls had been well established. However, the reporters themselves, small unstructured peptides, were of limited utility. Under the guidance of Dr. Miklos Guttman and with the assistance of many brilliant and rather patient friends and colleagues I have been able to develop novel imidazolium based IERs. This document will describe the design, validation, and subsequent refinement of these compounds through the discussion of previously published and ongoing work
Consequences of Chronic Huntingtin Knockdown in vivo
No full textHuntington’s disease arises from a toxic gain of function in the huntingtin (HTT) gene. As a result, many HTT-lowering therapies are being pursued in clinical studies, including those that reduce HTT RNA and protein expression in the liver. To investigate potential impacts, we characterized molecular, cellular, and metabolic impacts of chronic HTT lowering in mouse hepatocytes. Lifelong hepatocyte HTT loss is associated with multiple physiological changes, including increased circulating bile acids, cholesterol and urea, hypoglycemia, and impaired adhesion. HTT loss causes a clear shift in the normal zonal patterns of liver gene expression, such that pericentral gene expression is reduced. These alterations in liver zonation in livers lacking HTT are observed at the transcriptional, histological and plasma metabolite level. We have extended these phenotypes physiologically with a metabolic challenge of acetaminophen, for which the HTT loss results in toxicity resistance. Our data reveal an unexpected role for HTT in regulating hepatic zonation, and we find that loss of HTT in hepatocytes mimics the phenotypes caused by impaired hepatic β-catenin function.Funding provided by CHDI Foundation grant to JBC, NINDS grant NS124728 to SZ, NIDDK grants R01DK062277 and R01DK103775 to SPM, and diagnostic and technical assistance for liver histology was provided by Pittsburgh Liver Research Center’s Clinical Biospecimen Repository and Processing Core which is funded by NIDDK grant P30DK120531 (PI: SPM)
Interpretation of a temperature and salinity section at 180 degrees longitude in relation to the ENSO cycle in the equatorial Pacific for March 2023
No full textEl Niño-Southern Oscillation (ENSO), which is the cycle consisting of El Niño and La
Niña has major global impacts on climate. El Niño and La Niña are characterized by large
changes in temperature in the equatorial Pacific, and understanding these changes is vital for a
broader understanding of global climate. The goal of this study is to place data collected on a
cruise conducted in early March 2023 in a broader context, comparing features such as 20°C
isotherm depth, surface temperature, and barrier layers. Data used for this paper was collected
from March 3rd to March 7th of 2023, along the International Date Line from 5°N to 5°S. Cruise
data was more similar to La Niña conditions than El Niño conditions, but still had significant
differences when compared to La Niña data collected from a Tropical Atmosphere Ocean (TAO)
array. Thermoclines were deeper in El Niño conditions when compared to La Niña conditions,
but the cruise data had thermoclines significantly deeper than La Niña data in the TAO. A barrier
layer was found at 5-4°N, and a salinity maximum was found near 1-5°S, which matched
observations reported in a previous study
Affective Anti-Racism Learning: Navigating Anger in a Mutual Aid Group
No full textThesis (Master's)--University of Washington, 2023Within the learning sciences, affect has often taken a backseat in literature even though it is inextricable from our learning processes. In this paper, I explore the affective dimensions of learning anti-racism, exploring a person’s affect while they takes action towards materially benefiting a racially oppressed group. I present data from conversations I had with research partners (n = 3) about their experiences acting with the intent to materially benefit BIPOC. Informed by ethnographic methods, we had weekly one-hour conversations for over a month and a half to hone in on their affective anti-racism learning. Here, I focus on one research partner’s experience working with a mutual aid group in Seattle and distributing resources to unhoused residents at an encampment. We had conversations about her emotional responses, particularly anger, when she learned that a police sweep was about to happen to the encampment. Findings from this study motivate further theorizations of affect and anti-racism learning with the affordances of present learning theories
Advancements in Optical Coherence Tomography: Innovations and Applications for Ophthalmology and Dermatology
No full textThesis (Ph.D.)--University of Washington, 2023Optical coherence tomography (OCT) is a well-established imaging modality widely used in ophthalmology and is emerging as a valuable clinical tool in dermatology. OCT angiography (OCTA), an advanced extension of OCT, utilizes intrinsic blood flow movement to generate angiographic images beneath the tissue surface, eliminating the need for contrast agents. This thesis demonstrates the capabilities of OCT in high-resolution imaging of 3D structures and microvasculature in the human eye and skin under diverse conditions.
The opening chapter of this thesis serves as an introduction to OCT technology, providing a foundation for the subsequent chapters. In Chapter 2, we delve into novel algorithms and methods developed for OCT imaging. We begin with a straightforward yet highly effective approach for estimating the optical attenuation coefficient (OAC) from OCT images. OAC not only enhances OCT imaging contrast but also serves as a valuable physical parameter for assessing tissue properties, as alterations in tissue morphology and content can impact OAC. Building on this, we leverage the OAC to enhance OCT imaging contrast, leading to the development of algorithms for more precise and efficient segmentation of epidermal thickness in the OCT imaging of skin tissue, and retinal pigment epithelium (RPE) and calcified drusen in the imaging of retina tissue. Additionally, we introduce TransUnet, an innovative deep learning-based method developed for accurate segmentation of the outer retinal layer (ORL). Through this progressive exploration of OCT technology and advanced algorithms, our research significantly improves imaging segmentation and analysis in OCT clinical applications.
Building on this foundation, Chapter 3 showcases the remarkable capabilities and potentials of OCT in clinical ophthalmology. Firstly, we investigate the symmetry of interocular choroidal thickness and vascularity index measurements in normal eyes using SS-OCT, finding choroidal differences between normal fellow eyes in adults without obvious pathology. This study aids clinicians and researchers in distinguishing expected asymmetric changes in normal eyes from changes associated with diseases. Secondly, we examine variations in the ORL thickness among different stages of age-related macular degeneration (AMD), revealing significant differences in ORL thickness measurements among various AMD stages, indicating the potential of ORL thickness as an independent biomarker for predicting AMD progression.
Lastly, in Chapter 4, we discuss the clinical applications of OCT for dermatology. Firstly, we integrate pressure sensors with a handheld probe to facilitate imaging of micro vasculature, addressing the challenge of uncontrollable mechanical stress during contact mode imaging of the skin. This handheld scanning probe with built-in pressure sensors provides real-time feedback to control the mechanical stress, enabling repeatable and reliable OCTA images for a more accurate investigation of skin conditions. Secondly, we employ a clinical-prototype OCT system to image severe burn wounds at multiple scan sites across two time points. Quantitative analysis of vascular area density and surface roughness offers key insights into the pathophysiological mechanisms responsible for wound healing, potentially serving as critical biological indicators in future clinical evaluation and monitoring of wound healing. Lastly, we demonstrate the potential of OCT alongside OCTA to non-invasively image and monitor human skin graft health and integration over time, providing valuable insights for wound healing monitoring after skin graft surgery.
In conclusion, this thesis contributes to the advancement of OCT technology through the development of novel algorithms and its applications in clinical ophthalmology and dermatology. The research presented here significantly enhances imaging segmentation and analysis in OCT and offers valuable insights for disease diagnosis and monitoring in ophthalmology and wound healing evaluation in dermatology
Phenotyping and Immune Signaling of Monocytes and Macrophages in Porous Precision-Templated Scaffolds
No full textThesis (Ph.D.)--University of Washington, 2023Porous precision-templated scaffolds (PTS) are three-dimensional biomaterial constructs where the pore size and pore interconnects can be precisely controlled, allowing for the creation of scaffolds with tunable characteristics and implant outcomes. Regardless of the polymer used in construction and without the use of any signaling/stimulating molecules, PTS with uniform, interconnected, 40 μm pores have shown a remarkable ability in immunomodulating resident cells for tissue regeneration. In contrast, PTS with smaller or larger pores result in a pro-inflammatory and pro-fibrotic foreign body reaction. The mechanism behind the pore-size-mediated phenomenon remains unclear; however, monocyte and macrophage phenotypes have been identified as key mediators in regulating the implant outcome within the PTS. Here, we quantify the infiltration kinetics and functional response of circulating monocytes to subcutaneously implanted PTS. We then identify the regulatory roles of MyD88-dependent signaling downstream of Toll-like receptors (TLRs) that drive the regenerative, pro-healing response in 40 μm PTS. Finally, we demonstrate a synergetic relationship between TLR signaling and macrophage receptor with collagenous structure (MARCO), an innate activation marker of monocytes and macrophages, in modulating macrophage phenotype. Overall, these findings further our understanding of the molecular mechanisms underlying cell behavior and tissue regeneration in PTS and implantable biomaterials
Interactive AI Model Debugging and Correction
No full textThesis (Ph.D.)--University of Washington, 2022While the accuracy of Natural Language Processing (NLP) models has been improving, users have expectations beyond what is captured by standard performance metrics. For example, chatbot assistants should not provide inappropriate or unfair responses to certain types of inquiries, and translators should not sacrifice their support for languages with low resources for perfect performances in English. Unfortunately, existing models have various deficiencies (e.g., too sensitive to trivial input perturbations), thereby creating a gulf between “accurate models” (those that place high on leaderboards) and “successful models” (those that can support real world use cases). In this work, we argue that this gap exists primarily because we are not considering human needs sufficiently throughout the model development cycle. We present how the human perspective is missing across the model development and deployment, and address the issues by building tools to interactively help humans debug and correct models. First, the evaluation that developers conduct (e.g., holdout accuracy) does not reflect human expectations on how models should behave (e.g., models should be right for the right reasons). For experts to express their expectations regarding models, we provide them with domain-specific languages that allow grouping similar examples and performing counterfactual, what-if analyses, so that they can rigorously inspect the model on a variety of concrete capabilities. Second, the data that model developers collect for building an NLP model usually contains biases and distribution gaps, and does not reflect how humans will actually use the model. To compensate for human omissions in defining, collecting, and inspecting the intended data distribution, we build automated approaches (NLP text generators, automatic pattern mining and sampling algorithms) that can augment experts in collecting how humans use models. Third, the default interactions with deployed models do not allow end users to recover from AI errors. To make AIs more usable in downstream applications, we also design interaction strategies that help end users collaborate with deployed AIs in a transparent and controllable manner so they can detect and overwrite AI errors in real-time. Taken together, this thesis shows that when given strategies and tools to interactively massage (partition, perturb, and decompose) data throughout the machine learning model development stage, developers and end users can debug and correct AI models in a more comprehensive, less biased, transparent, and controllable way
“Just Going Without”: A Health Needs Assessment for Queer Women, Non-binary, and Transgender People in Seattle, WA
No full textThesis (Master's)--University of Washington, 2022Queer people (LGBTQIA+ people) face discrimination that negatively impacts their health. Research on queer health has tended to condense people of diverse queer identities into one group, meaning little is understood about the differences in health needs at different intersections of queerness. This trend has obscured the health needs of queer women, people of color, gender minorities (non-binary, genderqueer), and transgender people. The present study uses mixed methods to evaluate the health needs of queer women and non-binary people. Our findings indicate that queer women and non-binary people face considerable barriers when seeking health care services, across a broad spectrum of service types. Insurance and financial barriers were most ubiquitous, but transportation, hours, and queer competence also presented barriers that reduced access to care. This study improves our understanding of queer health needs and suggests areas for intervention to support queer health, but further research is needed
Farm system resilience during the COVID-19 pandemic: A survey-based analysis of impacts and adaptations among farmers in Washington State
No full textThesis (Master's)--University of Washington, 2022The shock of the COVID-19 pandemic caused many impacts in Washington’s farmingsystem including labor, distribution, processing issues coupled with changing economic and
consumer practices. In order to cope with these unforeseen issues, the farming sector had to
adapt their business practices accordingly. Resilience, or ability of a farm to continue business
functionality, is rooted in three primary capacities: robustness, adaptability and transformability.
To identify what impacts were most experienced by farms in WA state and adaptations they
instated to continue operation a survey was developed and deployed to farm owners and
operators in WA state between December 2020 to January 2021. This survey attempted to
identify how impacts and adaptations varied amongst farms in WA state based on specific
characteristics rooted in resilience attributes blanketed under the three primary resilience
capacities. Primary themes from collected data included how impacts varied greatly amongst
farms and how different farm characteristics could influence the flexibility, adaptability and
rapidity in which businesses were able to respond and/or adapt to these impacts