Glomeruli are the basic filtration unit of the kidney. The current understanding of its physiology is limited by the partial or 2D analysis of its structural components. The Vaughan Group uses optical super-resolution microscopy in combination with advanced chemical labeling techniques and powerful data analysis approaches to perform high-resolution 3D reconstruction of the whole mouse glomeruli. Overall, the work has the potential to provide a novel understanding of the glomerular structures and how they are altered in aged and diseased conditions. The labeling of the overall morphology of the glomeruli is achieved by chemically labeling the distribution of abundant macromolecules (carbohydrates, amine, and DNA) using Fluorescence Labeling of Abundant Reactive Entities (FLARE). Though we could visualize the general physiology of the sample with FLARE, incorporating specific targeting of molecules with FLARE is still challenging. My role is to optimize the FLARE protocol to add the capability of labeling the distribution of specific molecules using immunolabeling. The most challenging part is that all the fluorophores labeled prior to FLARE will be bleached out by the strong oxidation step while labeling carbohydrates. I am focusing on exploring possible workarounds to incorporate immunostaining with FLARE. The only way to bypass the bleaching fluorophores is to label dyes after the FLARE. However, the FLARE involves the gelation part, and the gel makes antibodies which are linked to fluorophores hard to get into the sample. So, instead of using regular secondary antibodies, I use biotin and then link to the streptavidin dye, which is smaller in size and easier to enter the sample. With this optimization working, we could incorporate whatever target of interest with high resolution on top of three general stains provided by FLARE, giving us an extra degree of information for our 3D reconstructions of glomeruli.

The kidney is composed of thousands of filtration units called nephrons. Within each nephron lies a tuft of capillaries, the glomerulus, that filters from the blood through a filtration barrier. Over time this filtration barrier thickens, ultimately causing decreased blood filtration. A main marker of this age-related degradation are telomeres which comprise the ends of chromosomes and protect the coding DNA from degradation. If telomeres become too short, the coding region of DNA will begin to degrade. To combat this, telomere shortening signals for cells to enter a state of permanent cell cycle arrest, senescence, which prevents replication of cells with degraded DNA. Accurately quantifying telomere length will enable the development of correlations between cell lineage and structural changes within the kidney. I hypothesize that Expansion Microscopy (ExM) and quantitative-Fluorescent In-Situ Hybridization (Q-FISH) will allow me to determine the relationship between physiological changes in the filtration barrier and single-cell telomere length. ExM enables a superresolution cellular view by embedding a tissue sample in a swellable hydrogel, achieving four-fold isotropic expansion. This technique confers greater resolution of Q-FISH signal versus traditional confocal microscopy. To determine telomere length, I developed custom analysis scripts to quantify Q-FISH signal brightness. Preliminary results indicate an increased brightness of younger mice compared to their aged counterparts. Additionally, to receive a base-pair output I compared the Q-FISH signal to the signal of a DNA region of known length, Major Satellites, determining young telomeres to have an average base-pair length of 30 kb. I am validating these results in collaboration with the Miller Lab using next-generation sequencing techniques. Future work includes concurrent application of general physiology stains to identify and measure the glomerular filtration barrier physiology. Results from this method will allow for a wealth of information regarding the relationship of single-cell telomere length and glomerular structural health.

Epigenetic factors, including histone marks, change the patterns of gene expression without altering the DNA sequence. Variations in such marks are known to account for the ability of stem cells to differentiate into various cell types, but a preliminary experiment conducted by a former member of the Vaughan Group, Dr. Marcus Woodworth, has revealed that even in a phenotypically homogeneous, terminally differentiated cell population, the presence of H3K27me3, a repressive histone mark, varies on the HOXC gene of human retinal pigment epithelium (RPE1) cells at single-cell, single-loci level. My role is to evaluate the two possible origins of such heterogeneity: inheritance (histone mark varies due to events that happened during differentiation, or the random drift after differentiation, and the variations are kept within each lineage of cells), and multiple mark co-repression (one histone mark varies, but summing its effect with another histone mark that perform a similar function lead to the observed functional homogeneity), and to validate that such pattern exists among a broader range of genes. To achieve these ends, I profile selected histone marks (H3K27me3 and H3K9me3) on genes that experience different types of regulations during differentiation (HOXC, GAPDH and SIX6), using imaging-based methods, including the time-lapse imaging of live cells to map out lineages, and expansion microscopy (ExM) to capture fluorescently labeled histone marks at single-loci level. If the hypothesized origins are true, a significant difference in the number of histone mark clusters around the genes of interest would be observed between cells of different lineages, and complementary variation patterns would be observed between H3K27me3 and H3K9me3. The study reveals the nuances of histone mark dynamics on the single-cell, single-loci level, and optimizes an imaging-based method that has the potential for multiplexing at high spatial resolution, thereby providing a powerful tool for further studies on epigenetics.

Achieving high performance in fixed-wing, unmanned aerial systems necessitates efficient wing assemblies which often entail significant design and production costs. Balancing measures associated with performance, production, reliability, and maintainability adds further complexity to wing design. I present here my current work on the use of Cellular Compressive Wing (CCW) architecture as a viable solution for achieving low structural mass and high flight efficiency while simultaneously enhancing production, maintainability, and reducing costs. To confirm the approach, a wing planform utilizing CCW has been developed based on specific aircraft performance requirements. Computational Fluid Dynamics and Finite Element Analysis have been leveraged to generate estimates of dynamic planform load distributions and CCW interface load characteristics. These simulation methods have in turn been used to guide the design of wing cell interfaces optimized for additive manufacturing techniques employing photopolymers and composite thermopolymers. Application-specific bench-test and in-flight hardware are currently being constructed and tested for direct experimental validation of dynamic planform and CCW interface loads.

NASA is currently developing communication infrastructure for the lunar landscape in preparation for its Artemis missions to the moon. When rovers explore remote areas on the moon, where radio signals may not reach, there is a need for methods to facilitate both communication from base camps and help the rover reconnect to the network. The goal is to develop a deep learning model to predict radio signal quality and maximize communication by autonomously relocating lunar rovers to areas with optimal signal strength. Channel State Information (CSI) data provides insight into how a signal propagates from transmitter to receiver, including data for the signal magnitude, phase, and ray interactions with the environment. I investigate feature selection methods with different combinations of simulated CSI data to train our Recurrent Neural Network (RNN) deep learning model and analyze the resulting performance. Previous research demonstrates one way to improve the prediction of a model is by utilizing information at the hidden layers, the internal layers between input and output data. I explore this method and aim to capture patterns over time with our CSI input data and RNN architecture for predicting the magnitude of the next ray hit. We expect that using additional information at hidden layers will help us understand the relationships between input data and help optimize the model. We anticipate validating the model through the use of real CSI data using physical experiments to replicate signal interaction in a lunar environment. Our work contributes to the development of communication technologies for upcoming lunar explorations. It also provides insight into the role deep learning can play in radio frequency propagation, paving the path for further research in this area.

Proper chromosome segregation in mitosis relies on the correct attachment of kinetochores to the plus ends of microtubules. Kinetochores are protein complexes that assemble onto centromeres and bind microtubules. Microtubules are dynamic polymers of 𝛼- and 𝛽-tubulin subunits with an intrinsic structural polarity due to the repeated head-to-tail orientation of the heterodimer subunits in the lattice. This polarity results in a faster growing plus end and a slower growing minus end. Kinetochores are thought to initially bind to the microtubule lattice and then achieve plus end attachment by the action of plus end directed motor proteins or by the microtubule tip disassembling to the attachment point. While the plus end attachment is essential for mitotic fidelity, it remains unknown if the kinetochores themselves have an intrinsic polarity preference. Using total internal reflectance fluorescence microscopy, we have found that individual kinetochores assembled on centromeric DNA have a strong preference for binding the plus ends of stabilized microtubules in the absence of motor proteins and ATP or microtubule dynamics. Furthermore, using optical trapping we are able to measure the rupture forces of kinetochores on both ends of microtubules and have found that the observed preference for plus ends is matched by a greater binding strength at plus end tips. These results together give insight into how kinetochores could efficiently form plus end tip attachments and how they likely play a part in cell cycle regulation by using tension to sense a correct attachment. A better understanding of the specific mechanisms of kinetochore microtubule binding is valuable for understanding control of mitotic progression and could potentially inform more targeted anti-cancer therapies that focus specifically on dividing cells without impacting regular cell function.

Marine microbial communities produce and cycle organic matter in the ocean. Some of this organic matter is in the form of metabolites, small, organic biomolecules that are present both inside of microbial cells and dissolved in seawater. Studying metabolite dynamics provides insights into the fate of a significant portion of marine primary production as well as microbial community interactions that influence short and long term carbon storage in the ocean. Here I analyzed both dissolved (extracellular) and particulate (intracellular) metabolites from the 2019 Gradients 3 (G3) research cruise that were collected along a latitudinal transect. Sampling stations spanned the North Pacific Subtropical Gyre, an area with low nutrients and primary productivity, to the North Pacific Subpolar Gyre, an area with higher nutrients and primary productivity. I extracted particulate metabolites using a modified Bligh and Dyer extraction and dissolved metabolites using cation-exchange solid phase extraction. I acquired metabolite data using liquid chromatography mass spectrometry and processed the data using Skyline software. In both dissolved and particulate samples, metabolite pools were dominated by compatible solutes, compounds organisms use for handling osmotic stress, as well as amino acids. Metabolite abundances in both phases largely increased traveling northwards along the transect, reflecting increases in productivity, microbial biomass, and nutrients. However, certain metabolite concentrations did not follow this trend, suggesting that differences in microbial community composition or physiology may play an important role in regulating the synthesis of these compounds. These results show how varying environmental conditions affect the composition of organic matter produced by marine microbial communities. This information can be used in to predict how marine primary producers will store and use carbon in a future changed ocean.

Quantum dots are nanometer scale semiconductor particles that have been extensively studied over the past decade. Colloidal quantum dots are dispersed in solution, and so can be easily deposited on a surface. This allows them to act as highly versatile quantum sensors. I am studying cadmium selenide quantum dots doped with manganese (Mn:CdSe). They possess a spin of 5/2, meaning they have six spin states, each corresponding to a different quantized energy. These six energies can be probed with photoluminescence spectroscopy, and theoretically appear as six distinct peaks in the spectrum. This allows us to use spectral analysis to read the spin state of a dot. Due to the Zeeman effect, the spin state energies are sensitive to applied magnetic fields. A simple sensing procedure first initializes the spin state, allows it to evolve under some magnetic field, and reads out the final spin state. My work focuses on the initialization and readout of the spin. For this purpose, I previously built a monochromator to characterize the quantum dots under pulsed excitation at various wavelengths, power, and temperature. I am measuring their properties using photon counting correlation measurements, photoluminescence spectra, and lifetime measurements. The goal of these results is to characterize the properties of these Mn:CdSe quantum dots to lay the groundwork for their development as a highly sensitive quantum sensor.

Using data from the United States Sentencing Commission (2014-2022), this study analyzes the impact of a defendant's gender in the sentencing of federal homicide cases. Previous research shows that female defendants experience leniency in criminal sentencing compared to male counterparts. However, studies also suggest harsher punishments are given to female defendants when the crime is violent. This may be influenced by the social construct of gender, where traits including aggression and violence are perceived to be inherently male, and male violence is often expected and excused. Focusing exclusively on federal homicide cases from fiscal years 2014-2022 (N = 3017), I ran linear regression analyses controlling for legal and extralegal factors to analyze the effect of gender on sentence length. I hypothesize that in the case of federal homicide, male defendants will receive shorter sentences compared to female counterparts. This study focuses how gender influences sentencing outcomes in federal courts. It is crucial to understand how gender influences judicial sentencing in order to promote a just legal system.

Accurately modeling atmospheric re-entry has become incredibly important with the advent of reusable spacecraft. Computational Fluid Dynamic (CFD) employs solvers, a combination of mathematical models, to attempt to replicate real-world physical characteristics, such as when a spacecraft is re-entering the atmosphere. This research attempts to validate the OpenFOAM hy2Foam solver–which was created to model the environment of atmospheric re-entry–by comparing CFD results to real-world wind tunnel data of the hypervelocity ballistic model 1 (HB-1) at mach 5.1. We show with 99% confidence that the CFD simulations do not produce numerically accurate results when compared to historical wind tunnel data at seven varying angles of attack: -1, 0, 2, 4, 6, 8, 10, and 12 degrees. For all angles of attack, the forebody axial-force coefficient disagrees with historical wind tunnel testing, being 2.38 times less on average. Additionally, for all but the -1 and 0 degree angle of attack, the pitching-moment coefficient disagrees with the historical data, being 52.6 times less on average. Additional research conducted on the HB-2 model has found similar disagreement of aerodynamic results demonstrating a need for additional research to ensure the solver produces numerically accurate results. Accurate solvers are vital to ensure that CFD simulations accurately model real-world conditions, such as during spacecraft re-entry when safety of astronauts could be at stake if a spacecraft is designed based on invalid data. 

This poster describes a qualitative study highlighting the intersection of ethnic identity and Christian faith in shaping South Asian college students’ perceptions of LGBTQ+ individuals. Current sociopolitical climates toward LGBTQ+ individuals in South Asian countries tend to be hostile, and even South Asian communities within the United States can reflect similar beliefs. Zaidi (2014) found that shame in the South Asian community was in conflict with a desire to express one’s queer identity among South Asian youths (Zaidi, 2014). Moreover, environmental factors such as the religious setting might contribute to varying perspectives regarding LGBTQ+ individuals; in the current study, we highlight faith-based higher education institutions (i.e., Christian university) as an institution that can shape views regarding LBTBQ+ folks and their experiences. We conducted 6 semi-structured interviews with South Asian college students enrolled in a Christian university located in the Pacific Northwest region of the U.S. Our three-member research team transcribed the interviews, coded the transcriptions, and placed the codes in themes according to Braun and Clarke’s (2006) guidelines for Thematic Analysis. The four themes that we identified include support for LGBTQ+ people on campus, Christian messaging around LGBTQ+ identity, South Asian communities, and participant’s own attitudes. These major themes also included subthemes, some of which are campus advocacy and protests influenced participant’s beliefs, feelings of an internal struggle, attitudes of South Asian communities, and individual affirming attitudes. Broadly, we found that the participants viewed their own South Asian communities as generally silent or passive in LGBTQ+ dialogues, and that their Christian campus promoted both helpful and unhelpful conversations about the topic. We will present some implications for practice in higher education around fostering an inclusive space for LGTBQ+ individuals, especially as they pertain to intentional integration of culture-specific (e.g., South Asian) and religious (e.g., Christian) perspectives.