Family businesses are some of the most important economic contributors in the United States, accounting for approximately 64% of the U.S. GDP. The family business model, which refers to any business with two or more family members on the board or in ownership, is a crucial and enduring part of business in the Seattle area and abroad. Historians have often pointed out that the family business model seems to be the base model for business and has thus been present since the beginning of organized business, often in the form of farms, merchant companies, banks, and other small businesses. Despite its prevalence, the family business model is far from perfect because of its numerous commonly encountered limitations. One of the limitations family businesses face is the challenge of succession, as only about 30% are able to succeed from the first generation to the second. Other limitations relate to growth, sustainability, and qualification problems. This study, conducted as a literature review, uses a combination of peer-reviewed articles and popular sources (chosen based on criteria of relevancy and prominence) as quantitative data to examine the consensus of family businesses in Seattle and the solutions that have been proposed to address these limitations. Interviews with family business owners in the Seattle area were also conducted to provide qualitative data and to highlight specific opinions. The economic and historical implications of Seattle family business are also discussed. This research aims to provide insight into otherwise costly financial, succession, and leadership difficulties in order to ensure that the family business model is an enduring contributor to the Seattle economy. Having the proper knowledge on how to approach these difficulties and reconcile with their seemingly conflicting nature can help family businesses in the Seattle area thrive while working through complicated business situations.

The effective treatment of individuals with HIV relies on maintaining therapeutic drug concentrations, necessitating accurate measurement of antiretroviral (ARV) drug levels. Current methods, such as liquid chromatography tandem mass spectrometry (LC-MS/MS), are limited by cost and accessibility. Our research addresses this gap by developing the INTEGRase activITY (INTEGRITY) assay for measuring integrase strand transfer inhibitors (INSTIs), a leading class of ARV drugs. This 2-step assay quantifies INSTIs using a DNA strand transfer reaction and quantitative polymerase chain reaction (qPCR). The presence of INSTI drugs disrupts the strand transfer reaction, inhibiting full-length target DNA formation, which is then measured through real-time qPCR. My work focused on optimizing the limit of detection of INTEGRITY by altering the strand transfer reaction conditions and protocol. Specifically, I conducted experiments altering INSTI drug concentrations and optimizing pre-incubation times of integrase with the drug to enhance the LOD. I observed that preliminary incubation of integrase and INSTI drugs for 5 minutes at 37 degrees Celsius improved the LOD of INTEGRITY by an order of magnitude. The simplicity of the INTEGRITY assay, utilizing standard laboratory equipment, holds immense promise for broadening access to routine clinic-based ARV drug level monitoring. This advancement has the potential to significantly enhance HIV care on a global scale by offering a cost-effective and accessible solution for monitoring therapeutic drug concentrations.

Prostate cancer is the most common type of cancer amongst men in the U.S. It relies on androgens that bind to the androgen receptor (AR), which increases the transcription of genes associated with the growth and proliferation of the prostate cells. For the AR-driven prostate cancer (ARPC), current treatments involve decreasing androgen levels (Androgen Deprivation Therapy) or inhibiting the ARPI (Androgen Receptor Pathway Inhibitors). However, around 15% of patients develop resistance to these treatments, resulting in a type of prostate cancer called neuroendocrine prostate cancer (NEPC). NEPC cells are no longer dependent on AR activity, which makes this subtype difficult to treat with the current treatment options in the clinic. To better understand the biology of NEPC, we focused on gene expression at the protein synthesis level and found that NEPC has a decreased level of a tRNA called Arg-TCT-1-1. Following Arg-TCT-1-1 tRNA overexpression in NEPC, we detected elevated expression of AR downstream targets via qPCR and western blot. NEPC with high Arg-TCT-1-1 also responded to an AR inhibitor called enzalutamide as measured by cell viability assays. To further investigate the role of Arg-TCT-1-1 in prostate cancer, we used shRNA-mediated knockdown of this tRNA in prostate cancer cells with high AR expression and measured changes in gene expression. This study will provide important insights on the role of Arg-TCT-1-1 during the differentiation process from ARPC to NEPC.

Each winter, the northeastern U.S. experiences powerful storms that cover cities in snow and ice, which result in millions of dollars in damage, halt travel, and disrupt essential services. Yet, the type, intensity, and distribution of precipitation is unique to each winter storm. This research project aims to provide a greater understanding of the precipitation properties and distribution in snowstorms, through focusing on a major winter storm that occurred over the Midwest on 17 February 2022 and was the target of a research flight conducted during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS) field campaign. Radar data collected during this research flight provides a unique perspective of the vertical cloud and precipitation structure, and numerical model fields provide the environmental context of the structures observed in the radar measurements. This storm had a frontal boundary, or a strong thermal contrast, that provided lift needed for the production of precipitation and had sub-freezing temperatures so that the precipitation fell as snow.This frontal boundary consisted of warm air originating from southern latitudes riding over colder air originating from northern latitudes. Analysis of the vertical cloud and precipitation structure from radar data and the in situ cloud particle measurements collected during the flight revealed that regions of higher reflectivity had larger particles and greater ice water content, compared to regions with lower reflectivity. The analysis also includes examining how the cloud particle properties are different depending on the origin of the air masses (from the north or south) that form the storm. By relating the temporal and spatial information regarding the air masses to the high-resolution radar and microphysics data collected by the IMPACTS airborne instruments, the results of this analysis will ultimately support increasing the accuracy of snow prediction.