Chronic pain is a perplexing and complex disease that may inflict physical disability or psychological impairment on individuals due to a medical illness or intervention, acute injury, or in the absence of physical illness or injury. Yet while chronic pain affects individuals across all age ranges, certain groups are disproportionately represented in chronic pain research. In particular, limited chronic pain research has focused on adolescents and young adults (AYAs) roughly between the ages of 16 and 25, leaving unanswered questions about how and when AYAs with chronic pain achieve developmental milestones such as gaining employment, forming romantic relationships, and living independently. The focus of this project is to investigate the effects of chronic pain on AYAs and aims to answer the following research questions: (1) Does the age of onset of chronic pain influence how AYAs achieve developmental milestones, (2) What developmental milestones are achieved by AYAs with chronic pain and how do they compare to controls who experience no chronic pain, and (3) Are commonly applied psychological measures ascertaining the most important information from AYAs? To answer these questions we performed a secondary data analysis of a data set of AYAs reporting to a tertiary pain center in the United Kingdom. This data set is courtesy of Dr. Hannah Twiddy of the University of Liverpool. Our analysis includes questionnaire data in the form of validated measures for impacts of pain on lifestyle, disability, depression, and self-esteem among others.  Results of this study describe the developmental milestones achieved by AYAs suffering from chronic pain and will help psychologists understand the nature of chronic pain in AYAs, and potentially develop more effective treatment plans in the future.

At the 2017 Undergraduate Research Symposium, I presented a low-cost, automated device for influenza detection that was being developed in the Yager lab. After creating, testing, and optimizing this device, we were left with many questions. While certain components of fluid flow in paper are understood, there is much more to learn. In this device alone, three different types of paper were used to run the two-dimensional assay. Current unanswered questions include the following: how do additives affect protein deposition, rehydration, and capture? How much of a dried protein on paper can be rehydrated by a passing solution, and which paper and solution properties affect this value? How do the viscosity and complexity of our patient samples affect the quality of our results? Our overall goal is to determine how to optimize our test line and generate a better understanding for optimization of future diagnostic devices. To make progress towards this goal, my project centers on the development and characterization of a laboratory technique to quantitatively study the effects of these parameters on protein interactions with membrane surfaces and other proteins bound to those membrane surfaces. Improving our understanding of these interactions in membranes will enable better diagnostic device optimization and enable illness detection with lower amounts of infected sample – allowing for earlier detection and better disease treatment. Through the development of this testing apparatus, I have begun to address these questions.

Lateral flow tests are assays conducted on porous media, commonly referred to as paper, that can detect and quantify analytes in a sample. They have the potential to return results within minutes and can be used in low-resource or non-medical settings. Protein adsorption is critical in these tests because protein interaction with a media can affect the delivery of reagents or choice of blocking agents to prevent nonspecific binding. A computational model of the fluid and adsorption physics may improve the development of paper-based assays. Yet-to-be-published data from the Yager group evaluates protein adsorption based on the deposition and analysis of protein spots on paper. The computational model used is derived from Darcy’s law, commonly used to model fluid flow in porous media and to calculate volumetric flow rates. This model makes two main assumptions: the porous media is fully saturated, and there is zero outflow on the boundaries of the media. These assumptions are not applicable because the protein spot dries as a result of evaporation, creating a non-zero outflow at the surface of the paper. The saturation level in the paper will also vary therefore Darcy’s law is not an adequate representation of the paper. My project aims to develop a more accurate computational model of fluid and protein absorption dynamic by modeling protein spots on paper. I incorporated an evaporation component that will allow the use of Richards equation to model fluid flow, which applies to unsaturated conditions. This is coupled with a protein transport and adsorption component to achieve a complete model. Although literature on evaporation from sand or soil is abundant, these results cannot be directly applied to evaporation from paper. This model will aid the diagnostic community in better understanding their assays and ultimately help improve the sensitivity and specificity of their assays.

This project aims to create a comprehensive park master plan for the transformation of the City of Westport, WA’s Pacific Ave property into a functional public park by utilizing principles of ecological restoration and community-based restoration. The City of Westport recently finalized its Comprehensive Park and Recreation Plan. Within the plan, the Pacific Ave property is zoned as a park, but is not currently used as a public park and has no intention of redevelopment by the city in the near future. The underutilized site has served many important uses throughout its history, and is located on the shore of the Elk River with a beautiful panoramic view of the bay and the mountains. The master plan is focused on research regarding site restoration with an assessment of the needs of both the community and the City of Westport. The information gathered through research and community engagement meetings will be synthesized into a master park plan for the Pacific Ave Property that will be presented to the Westport City Council in order to pursuade them to pursue funding for the project. This parcel holds historic and aesthetic value, and with restoration, it can be turned into a unique and valuable asset for both the city and the community.

Many membranes spontaneously demix into coexisting liquid phases. These include membranes that are as simple as three-component lipid vesicles and as complex as protein-rich vacuole membranes within living yeast cells. The resulting membrane phases are enriched in particular lipids and proteins. Membrane phase separation is one of several mechanisms proposed to explain the observation of heterogenous distributions of lipids and proteins in cell membranes ("rafts"), which are thought to be important in cell signaling, apoptosis, and protein regulation. The overwhelming majority of experiments that probe phase separation in membranes uses only one type of lipid (namely phosphatidylcholine). However, it is known that biological membranes also contain significant fractions of other kinds of lipids (e.g. phosphatidylethanolamine, or PE-lipids). An experimental challenge is that membranes composed of high fractions of PE-lipids are unstable – the lipids assemble in tubes instead of lying in sheets. In my project, I am [1] determining the maximum amount of saturated and unsaturated PE-lipids that can be incorporated into stable membranes, [2] measuring the temperature at which the membranes demix into coexisting phases, and [3] imaging the vesicles by fluorescence microscopy. Results from Aim 1 inform future researchers which lipid ratios they can use to produce stable membranes. Results from Aim 2 provide data against which the scientific community can calibrate molecular dynamics simulations. Results from Aim 3 provide a direct test of a recent prediction that PE-lipids should be anti-registered across fluctuating membranes.

Credible threats of nuclear war have not been as profound as they are in the society of today, since the Cold War. The nuclear tension between North Korea and the United States has been escalating at an alarming rate. As a resident of Seattle, I am living in the target area of a potential strike. As a United States Marine, I am one of the first to go when our Nation calls. But what is the likelihood of us actually engaging in nuclear war? Is Kim Jong-un really an insane dictator— lost in his own version of reality, or is he an intelligent and calculating leader attempting to influence the world around him? By using something from the social sciences called game theory, we can break away from the speculation in the media and systematically begin to understand the problem. We can analyze the people involved, their preferences and expectations, and what available actions they can take to achieve these goals. By attaching a theoretical payoff to every action a nation may take, such as North Korea or the United States, we can compare the possible outcomes and accurately predict the course of action by relying on two fundamental theories— first that people are rational. And secondly, that people are always looking to rationally maximize their utility. Through my research, I have found that when you analyze a leader like Kim Jong-un, you realize that his actions, however brash or combative they may be perceived, are actually rational choices. Furthermore, his decision to progress his nuclear program is also rational. Despite that, the crux of my research is that nuclear war with North Korea is currently very unlikely. Using the models from game theory, I can change this assertion from one that typically comes from speculation, to one of calculation.

Ovarian cancer is the deadliest of gynecological malignancies, with approximately 70% of patients diagnosed at an advanced stage of disease. With the current standard of care, cytoreductive surgery plus chemotherapy, the relapse rate is about 70% and the 5-year survival rate is less than 50%. Innovative therapeutic interventions are greatly needed, and one promising new strategy mimics the body’s endogenous anti-cancer immune response. This immunotherapy approach uses donor T cells engineered to express a T cell receptor (TCR) that is specific for a tumor-expressed antigen. Mesothelin (MSLN) is a validated antigen target, frequently over-expressed in cancer cells compared to healthy tissues. Using the mouse ID8 ovarian tumor model, we found that T cells engineered to express a high-affinity MSLN-specific TCR can kill ovarian cancer cells. However, the T cells lose effector function over time, which correlates with increased expression of the T cell inhibitory receptors PD-1, Tim-3 and Lag-3, markers of T cell exhaustion. Signaling through inhibitory receptors is stimulated by respective ligands that we showed are present in the tumor microenvironment (TME). Blocking these “immune checkpoint” signals can improve T cell proliferation and anti-tumor function within various TMEs. By applying checkpoint blockade, we hypothesized that both donor and endogenous T cells will have prolonged longevity and increased effector function in our ovarian cancer model. In ongoing studies, ID8 ovarian tumor-bearing mice received MSLN-specific T cells plus antibodies that block PD-1, Tim-3 and Lag-3 checkpoints; T cell phenotype and function were characterized at early and late time-points. We will discuss our findings and the potential relevance of this combination immunotherapy as a clinical treatment of ovarian cancer.

Joubert syndrome (JS) is a rare recessive genetic disorder characterized by hindbrain malformations appearing as the “molar tooth sign” on axial brain imaging. Causal genetic variants for JS need to fulfill three criteria: They need to be 1) rare, 2) deleterious, and 3) present in both alleles in the patient. Patients in our cohort are sequenced for rare predicted-deleterious variants (RDVs) to identify variants that satisfy the first two criteria. To determine whether the segregation pattern of the variants satisfies the third criterion, we sequence both parents, each of whom should carry only one of the variants. My research uses Next-Generation Sequencing to determine the segregation pattern for families in whom RDVs have already been identified. Specifically, I performed targeted-sequencing of putative causal variants in the parents using molecular inversion probes, and then I used the sequencing data to determine the segregation pattern. In most families, one RDV will be present in each parent, indicating that they affect both alleles in the child, because these variants are robust candidates that have passed the filters for being rare and deleterious. If both RDVs are present in one parent, then they have to be on the same allele and cannot be the cause of JS in the family. In these families, we will have to consider other variants or perform additional sequencing to identify the causal variants. Ultimately, the goal of my research is to elucidate the genetic basis of JS to improve prognostic and risk recurrence information, provide diagnostic, carrier and prenatal testing, and delineate the biological mechanisms of JS that will be the targets of future precision therapies.

Enormous outpourings of energy blasted into space by an accreting supermassive black hole (SMBH) are known as quasars. Previously, it was believed that SMBH’s enter a quiet state, thus extinguishing the quasar, over thousand-year-timescales. Changing-look quasars (CLQs) are a recently discovered, rare type of quasar that have been observed to transition far quicker than was thought possible. These short timescales motivated researchers, including ourselves, to reconsider our understanding of accretion phenomena in quasars to better understand what is driving the unexpectedly rapid changes observed in these CLQs. It is essential to establish a larger, more comprehensive, and less biased catalog of CLQs than currently available to answer such questions; and our work emphasizes creating this catalog. Our research involves both visually comparing spectra from the Sloan Digital Sky Survey database to each other and to new Sloan observations in the interest of detecting variations that suggest the quasar has turned on or off between observations. Sierra Dodd has recently identified three extremely probable CLQ candidates, bringing us closer to an improved understanding of which key changes in spectra correspond to CLQs. Further work on our part will aim to discover additional candidates to enlarge the pool of discovered.