Efforts to find disease-modifying treatments for Alzheimer’s disease (AD) have met with limited success in part because they have focused on identifying a specific pathogenic mechanism targeted by a specific drug. AD is a complex disease mechanistically associated with multiple pathways of aging so the probability of effectively targeting all of them would be greatly increased by using drugs in combination, each targeting different pathways. Previous studies have shown that a novel cocktail of the anti-aging FDA approved drugs rapamycin, acarbose and phenylbutyrate prevents age-related cognitive decline in mice by targeting distinct pathways of aging. These findings provided the rationale to test this drug cocktail for ability to alleviate cognitive impairment in a mouse model of AD. Transgenic 5xFAD male and female mice, with multiple mutant amyloid precursor proteins and expression of pathogenic Aβ42 peptide, were fed diet containing all 3 drugs, while control mice were fed a non-medicated diet. After 8 months of treatment, preliminary observations suggest 5xFAD mice fed the cocktail diet performed better in a spatial navigation learning task compared to mice fed the control diet. Laboratory procedures to confirm these observations will include rtPCR and immunohistochemistry to identify differences in expression of specific protein biomarkers of aging pathways in the brains of treated versus control mice. More work would be needed but observations from this study might be helpful in designing potential investigations to alleviate early phases of AD in patients using drugs already approved for human use.

The SirT6 gene is protective against systemic aging by enhancing DNA repair, decreasing inflammation and epigenetic deacetylation, and maintaining efficient lipid and glucose metabolism. Studies have shown that SirT6 function gradually decreases with increasing age with a loss in protective mechanisms. The role of SirT6 in brain aging has not been well established, and would be of interest to determine possible therapeutic targeting for conditions of age-related neurological dysfunction including cognitive impairment and dementia associated with Alzheimer’s disease. A mouse line was obtained from the NIH National Mouse Repository with genetic inactivation of one allele of the SirT6 gene (SirT6-/+) resulting in a partial loss of function. Older aged mice were tested in a spatial navigation learning task for exploratory behavior and memory. SirT6-/+ mice were unable to find escape holes as quickly as unaltered littermates (SirT6+/+) with a P-value of 0.003 significance. This observation suggests that partial absence of SirT6 function is associated with cognitive impairment. Following cognitive testing, mice were humanely euthanized, and brains collected and formalin fixed for immunohistochemistry staining to identify specific biomarkers of aging pathways including gamma H2AX for DNA damage response, HDAC-2 for epigenetic alterations, MCP-1 for inflammation, nitrotyrosine for oxidative stress, and p21 for senescence. Stains will be digitally imaged and heat maps generated for quantitative analysis of specific areas of brains from SirT6-/+ and SirT6+/+ mice. Results are expected to provide new knowledge on the role of aging pathways in the downregulation of SirT6 and age-related decline of learning and memory, and insight into possible conditions for development of more severe neurodegenerative diseases associated with dementia such as Alzheimer’s disease.

Every winter, those residing within the eastern half of the U.S. are slammed by powerful storms that pound cities with snow – costing millions of dollars in damage, halting travel, and impacting businesses and schools. Yet, like a thumbprint, each of these winter storms are unique and they can possess a range of tracks, structures, and intensities. This research project aims to provide a greater understanding of the development of such storms and the causes of precipitation variability within them by focusing on a single storm that hit the Midwest on 17 February 2022 as a part of a research flight conducted during the Investigation of Microphysics and Precipitation for Atlantic Coast-Threatening Snowstorms (IMPACTS). I analyzed data from multiple sources to explore the large scale environmental conditions and the fine scale precipitation structure. The environmental conditions included a strong thermal contrast, or a frontal boundary, that provided the lift needed for precipitation as well as sub-freezing surface temperatures that allowed for precipitation to fall as snow. Analysis of the vertical cloud and precipitation structure from radar data collected during the flight revealed regions of higher reflectivity where snow was heavier than in other portions of the storm. Microphysical properties, such as particle sizes, shapes, and ice water content were different within the region of high reflectivity than outside it. Additionally, the strengthening front at the 700-hPa pressure level coincided with the localized region of enhanced reflectivity observed by the ground-based and airborne radars. The high-resolution radar and microphysics data collected by the IMPACTS airborne instruments are used to help identify precipitation-defining processes within these storms, and ultimately will increase the accuracy of snow prediction and remote sensing of snowfall from space-borne instruments.

 Subduction zones are regions where two tectonic plates converge, and one is forced underneath the other. They are the primary driver of plate tectonics, and a source of major earthquakes. These earthquakes occur at shallow depths where plates slide past one another quickly, but at greater depths, with higher pressure and temperature (PT) conditions, rocks behave more ductilely. The transition zone between brittle and ductile regions hosts slow slip events (SSEs), which accommodate motion between the plates during events that last months to years, as opposed to the seconds over which earthquakes occur. SSEs are an important mechanism for accommodating plate motion at depth, thereby affecting the occurrence of larger devastating earthquakes, but currently the processes which facilitate SSEs and the rocks that host SSEs are not well understood. By studying rocks formed in and ancient subduction zone from Santa Catalina Island in California, we can learn more about our own modern counterparts, as the rocks record the conditions where slow slip may have occurred. Using optical petrography and data from x-ray spectroscopy, I examine thin sections of epidote-rich blueschist from SSE PT conditions. Optical petrography allows me to characterize the mineralogy of this rock, and the x-ray data provide the chemical compositions of individual minerals. Using image-analysis software, I will pair these two datasets to estimate the bulk-rock chemical composition of my sample. These data will allow me to constrain the starting material (protolith) of this rock before it was metamorphosed in order to determine if it was originally a sedimentary or basaltic component of the subducting oceanic plate. Doing so will improve our understanding of the way in which rocks at those pressure-temperature conditions deform and chemically change to create the context in which modern SSEs occur.

Biological age generally occurs earlier or later than chronological age and can be used as a biomarker for aging intervention studies. The rate of wound healing is known to decrease with increasing age, such that a simple skin wound might demonstrate overall aging of all organs and tissues of the body. This concept was tested in a mouse model of wound healing consisting of a 2 mm through and through ear biopsy. Cohorts of male and female C57BL/6 mice at 5, 13, and 21 months of age were biopsied, and the area of closure measured over 3 weeks. Ear biopsy cores were used to obtain DNA methylation signatures to a database of age-related signatures to compare biological age. The 5-month-old mice showed a higher percentage of wound healing than the 21-month-old mice 2.5 weeks following the biopsy with a p-value of 0.04. DNA methylation results used to calculate expected wound healing percentage correlated with measured healing percentage with an R2 value of 0.82. Additional validation of biological age will use a computational paradigm to assess severity of age-related lesions on an inter and intra-organ basis. Preliminary observations from this study indicate that a simple skin biopsy procedure can be used to predict biological age, with important translational implications for the treatment and prevention of aging and age-related diseases.

Alzheimer’s disease (AD) is a complex neurodegenerative condition that commonly affects aged populations; therefore, increasing resilience to aging may increase resilience to age-related diseases including AD. To test this concept, a preclinical mouse study was designed to investigate the effects of anti-aging drugs rapamycin, acarbose, and phenylbutyrate in combination (cocktail) previously shown to delay aging phenotypes in mice. Cohorts of C57BL/6 mice, 22 months of age and of both sexes, were fed standard chow containing the drug cocktail or standard control chow for two months. Mice were then given an intravenous injection of a neuronal-specific adeno-associated virus (AAV) vector consisting of Aβ and phosphorylated (p) tau, the major pathogenic components of AD, or AAV sham, and followed for another three months. Mice were then tested for cognitive function using a spatial navigation learning task. Overall, AD mice treated with the drug cocktail showed faster learning times, specifically in trial 2 for females (p<0.05) and trial 3 for males (p<0.05), compared to AD mice not receiving the drug cocktail. Following humane euthanasia, brain tissues will be assessed for Aβ and ptau neuropathology and pathways of aging using a combination of special stains and digital imaging to determine the cellular and molecular effects of the drug cocktail. The preliminary observation that the drug cocktail can prevent cognitive impairment associated with the early stages of AD suggests that targeting resilience to aging has potential translational implications for the early diagnosis and treatment of AD in human patients. Future efforts will work to establish molecular evidence of these observations and validate results in additional models of AD.

From playing sports to driving a car, our brain constantly receives a barrage of complex visual information. Previous work shows that recognizing two things (e.g., words, animals) presented simultaneously is harder than recognizing one, suggesting that the brain has a limited ability to attend to multiple visual objects at once. In this project, I examine whether American Sign Language (ASL) experience affects sign recognition. Specifically, I hypothesize that signers and non-signers may differ in their ability to attend to multiple signs at once. Participants look at the center of a monitor where a reference letter sign appears, followed by test letter signs on both the left and right. On each trial, either the left or right sign is relevant (single-task condition), or both signs are relevant (dual-task condition). Participants respond, with a button, whether the relevant test sign(s) match the reference. The dual-task deficit (the difference in performance between single- and dual-task conditions) measures how well people can attend to multiple simultaneously presented signs. I compare the dual-task deficit across hearing non-signers, hearing fluent signers, and deaf signers. Previous work has shown a large dual-task deficit for written English letters and a small deficit for objects. I hypothesize that signers’ will have similar dual-task deficit to those of written English letters, while non-signers’ dual-task deficit will be small, similar to objects. So far, preliminary results from two non-signers support this second prediction. This project will reveal how the different sensory experiences and language demands of deaf and hard-of-hearing populations alter how their brains process visual information. Understanding these differences can help improve accessibility for these marginalized groups in public spaces. For example, it can help improve methods for presenting sign information to Deaf students to improve learning outcomes.

Cognitive decline with increasing age is an aspect of growing old. Age-related cognitive impairment (ARCI) entails the early stages of decline and is extremely common, affecting millions of older people. However, little is known about why some people have ARCI and some are cognitively normal at older ages. A recently characterized mouse model of naturally occurring ARCI, showing a distribution of affected and non-affected animals similar to older humans, was used to interrogate brain samples for transcriptomic profiles generated by RNA sequencing (RNA-seq). Hippocampal brain samples were collected from 22-month-old male and female C57BL/6 mice with and without ARCI (as determined by a spatial navigation learning task). RNA-seq was done by the NovoGene UC Davis sequencing Center. Preliminary data show a stronger presence of pathways of neurodegeneration and oxidative phosphorylation in the hippocampus of mice with ARCI compared to mice without ARCI. Detailed computational analysis will be done to investigate gene-expression quantifications using sequencing pipelines aligning Differential Gene Expression, KEGG orthology pathways, and Star RNA-seq read mapper in order to more accurately identify unique transcriptomic profiles in the brains of mice with and without ARCI. These findings will help identify genetic pathways that could be therapeutically targeted to ameliorate and possibly reverse the effects of ARCI, and provide insight into internal brain factors responsible for an increased risk in developing more severe conditions of neurodegeneration and dementia such as Alzheimer’s disease.

Possession Sound, WA, serves as an important foraging area for a group of seasonally resident gray whales Eschrichtius Robustus. This group of predominantly Eastern North Pacific Gray Whales that visit Possession Sound (Sounders) arrive as early as January and continue migrating towards other feeding grounds near May. If the frequency of sounds within the hearing range of these gray whales (50 to 5000 Hz) exceeds comfortable levels, they may have difficulty foraging. To monitor these relationships, we looked at the frequency and amplitude of sound near Mt. Baker Terminal (MBT) in Possession Sound, WA, from January 2021 to May 2021 with a specific focus on sounds from 50 to 5000 Hz. To gather this data, we used a SoundTrap 300 HF hydrophone, which is currently mounted to a dock at MBT. From January 2021 to February 2021, the hydrophone recorded continuously at a 96-kilohertz sampling rate. From March 2021 to May 2021, the hydrophone was set to record the first fifteen minutes of every hour at the same sampling rate. Preliminary research shows that Possession Sound has a consistent prevalence of ambient and intermittent noise within the established frequency range and peak amplitudes as high as 164 dB. This level of noise may have the potential to negatively affect gray whale behavior and foraging success. Future research should be conducted to see how current and future vessel slow-down trials will impact the frequencies and amplitude of local noise. Future research should also include comparing the MBT sound profile to other sites in the Salish Sea to better understand if the amplitude increase is unique to the area or a cause for wider concern.

The interaction between incoming salt water from the ocean, which is driven by tides, and exiting freshwater from rivers drives circulation through estuarine environments. As a result of the interaction between the incoming water and the exiting water, nutrients and sediment are moved around the estuary. This study focuses on the interaction between tides and the Snohomish River as it enters the Possession Sound estuary, located in Everett, Washington. To acquire data, I deployed a boat-mounted acoustic Doppler current profiler (ADCP), which uses sound to measure water current direction and velocity. I collected these data at varying tide stages at three different sites between the Snohomish River’s southern output to nearby Mount Baker Terminal, located 3.6 miles southwest of the river output. I have collected 8 samples over the course of 7 months at both ebb and flood tide stages. Each transect survey lasted 3-6 minutes and collected data from the first 20 meters of the water column. To get accurate analysis of current velocity and direction I split the data into categories based on depth. Preliminary analysis shows a southward current at many sites during all tide stages and depths. This raises questions about the scope of the river influence and the potential for southward currents regardless of tidal stage. However, further analysis of current velocity and river discharge are needed. Due to the complexity of the currents in the area, understanding how the river and the tides are interacting can provide a greater understanding of how these currents are impacting the dispersal of sediment and nutrients throughout the estuary.

The Everett Marina is a heavily developed area that has significantly altered water flow from the Snohomish River compared to its natural state. Anthropogenic alteration of this environment led to buildups of sediment, which has required dredging at increasingly shorter intervals leading up to the present. In order to explain sediment accumulation in the marina, this study examines the movement of currents and the abundance of sediment using an Acoustic Doppler Current Profiler (ADCP); data were recorded from June 2020 to August 2021 and compared to recent data I recorded from February and March of 2023. I hypothesized that current direction would be variable and speed would be sluggish due to the shallow depth. In addition, I hypothesized that seasonal changes such as snowmelt in spring and rain in winter would impact the velocity of the currents. Because sediment movement is largely impacted by currents, I hypothesized that sediment abundance would reflect seasonal changes in water flow. Analysis of water current data between June 2020 and August 2021 demonstrates a significant correlation between the velocity of North/South currents and the magnitude of tide stages, but river discharge levels appear to have less of an effect on current speed in the marina. The susceptibility of this area to tides more than river discharge suggests that it is easier for sediments to accumulate in one area as opposed to being swept away. Future analysis will compare this past data to the present and investigate potential correlations with sediment abundance.

One of the most striking adaptations in land plant evolution is the specialization of reproductive structures. LEAFY (LFY) is well characterized in flowering plants (angiosperms) as a transcription factor initiating the development of the flower, which contains the reproductive organs. LFY also regulates the first cell division of the zygote (diploid phase) in mosses (a type of non-vascular plant). The fern Ceratopteris richardii is a type of non-flowering plant that is midway phylogenetically between mosses and flowering plants, in the sister clade to seed plants. With a lab-friendly, independent haploid phase (gametophyte), transgenic protocols and a reference genome, C. richardii is ideal for studying LFY’s functional evolution. Previously, targeted silencing of the two fern LFY homologs CrLFY1/2, demonstrated that it maintains the identity of the apical stem cell in gametophytes. To further characterize the function of fern LFY, I study the effects of its over expression on gametophyte development. To that end, I record gametophyte development using bright-field and fluorescent microscopy. Preliminary results suggest that overexpression of CrLFY may affect development of the sperm-producing gametangia (antheridia) in fern gametophytes, with more antheridia found in transgenic plants late in development. Given that antheridia continue to be produced in wild type gametophytes in the absence of fertilization, I test the hypothesis that CrLFY overexpression causes delayed fertilization (by a yet unknown mechanism) and that increased antheridia represent a secondary effect. Here, I experimentally delay fertilization by withholding water needed for sperm release (“flooding”), and compare the number and pattern of antheridia on transgenic and wild type gametophytes with and without flooding. Functional characterization of LEAFY in a fern, and of other master regulators of development more generally, contributes to a better understanding of the evolution of land plants via the potential repurposing of ancestral genetic pathways into novel functions.

Deep learning methods for protein sequence and structure generation have shown remarkable success in many design scenarios when combined with structure prediction networks such as AlphaFold2. Despite this advance, many design challenges such as de novo binder design still haven’t been fully solved. Diffusion-based models have demonstrated considerable success in image and language generation yet their application in protein design has not yet been fully explored. Recently, the development of a protein diffusion model called RoseTTAFold Diffusion (RFdiffusion) has shown significant success in protein design and enabled us to explore the challenging problem of designing protein binders. Here I demonstrate utilization of RFdiffusion towards generation of de novo binders to disordered major histocompatibility complex (MHC) peptides. Specifically, we took an MHC peptide from KrasG12D and used RFdiffusion to generate a diverse range of structures that can bind this peptide. To optimize the sequence of these structures we used ProteinMPNN. We used AlphaFold2 to predict the structures of these optimized binders in complex with the peptide and saw promising interaction metrics. Further, structure prediction of the designs in complex with Kras wild type (WT) peptide resulted in lower AlphaFold2 confidence metrics of the interaction occurring. This is a promising preliminary result that RFdiffusion can generate fully de novo MHC-mimics, which can differentiate between neoantigens and WT peptide. Many cancers are caused by a single point mutation such as KrasG12D, thus, designing protein binders with point mutant specificity is exciting as it allows for targeting of disease causing proteins over healthy WT proteins. 

Racial and ethnic minority groups are less likely to seek or have access to mental health support services. Despite an increase in the quantity of mental health services nationwide, disparities in usage across racial and ethnic minority groups still exist, leaving resources underutilized and many individuals with unmet needs. Previous studies highlight both structural and non-structural barriers, such as income and stigma, which prevent certain racial groups from fully utilizing health care services. Studies often overlook health outcomes associated with immigrant status and overgeneralize findings to all populations. While scholars have studied the structural barriers to accessing mental health care services, there is a need to understand the cultural contexts preventing racial and ethnic groups from reaching out to these services. Using data from the National Health Interview Survey (NHIS), this study examines differences in access to and utilization of mental health care services of U.S born and immigrant populations from the years 2010-2020. The NHIS allows for the control and determination of effects of both structural and cultural factors such as health insurance coverage, financial instability, racial and ethnic characteristics, and migrant status to further understand the dynamics of access to and use of mental health care services. Foreign-born individuals are expected to show lower access to health care resources with varying levels of moderate mental distress. These differences are expected to vary for those who have spent more time in the U.S with more access to resources and higher levels of mental distress. Understanding trends related to mental health care can help develop better public policy responses and improve the promotion of health care services. This study will help address why services are underutilized and how to minimize health service inequalities among racial and ethnic populations. 

As part of cellular metabolism, all organisms produce reactive oxygen species (ROS), such as (O₂^– ) and hydrogen peroxide (H₂O₂). ROS can damage multiple cellular organelles and processes, disrupting normal physiology. Proteins, lipids, and nucleic acids can be damaged by ROS molecules, resulting in cell death. Also, several human diseases have been linked to an imbalance between ROS production and antioxidant defenses. Plants' chloroplasts and mitochondria contribute a substantial amount of ROS, as they are responsible for photosynthesis and aerobic respiration. In maize, Whirly ssDNA-binding proteins help to maintain the stability of the plastid genome. We recently demonstrated that maize seedling development is accompanied by increasing oxidative stress to the demise of chloroplasts, mitochondria, and their DNA. We also showed that maize seedlings grown in the light had higher levels of oxidants and lower levels of antioxidants than dark-grown seedlings. Here, our objective is to elucidate the role of Whirly proteins in oxidative damage. We isolated organelles from maize seedlings and performed oxidant and antioxidant assays for both wild-type and whirly-mutant plants. We found a significant difference in oxidation levels between wild-type and mutant plants. Our study should provide a better understanding of the role of ssDNA-binding proteins in oxidative damage to organelles.

A thoracic aortic aneurysm (TAA) is an expansion of the aorta within the chest. TAA can rupture, often causing sudden death. Mechanisms of TAA formation and growth are incompletely understood, but likely include dysfunction/loss of aortic smooth muscle cells and inflammatory cell accumulation. We hypothesized that quantitative analyses of cell types, transcriptomes, and cell-cell communications in experimental TAA tissue would provide insights into pathogenesis. Because many TAA are caused by heritable mutations, we investigated TAA pathogenesis in a mouse model of TAA caused by a mutation in the type 2 transforming growth factor beta receptor (Tgfbr2^G357W/+ mice). We used single-cell RNA sequencing (scRNA-seq) to quantify cell types and transcriptomes in proximal aortas of Tgfbr2^G357W/+ and wild-type mice. I analyzed transcriptomes with CellChat, a tool that uses scRNA-seq data to quantitatively infer and analyze intercellular communication networks. Tgfbr2^G357W/+ aortas had fewer smooth muscle cells and more macrophages than control aortas. Transcriptome analysis revealed that Tgfbr2^G357W/+ aortas also contained a new subpopulation of fibroblasts (“new fibroblasts”) that was absent in controls. Among all cell types, CellChat identified the new fibroblasts as the strongest source of outgoing cell-cell signals, and smooth muscle cells and macrophages as the major recipients of signals emanating from both the new fibroblasts and from other fibroblast populations. Outgoing signals predicted to emerge from the new fibroblasts are mediated by matrix components (e.g., collagen, laminin), cytokines (e.g., CSF), and other ligands (e.g., angiopoietin). We conclude that TAA in Tgfbr2^G357W/+ mice have fewer smooth muscle cells, more inflammatory cells, and a new population of fibroblasts. These new fibroblasts appear to signal to other aortic cells and may play important roles in inflammation and smooth muscle cell phenotypic alteration/loss. Further characterization of the new fibroblasts and their signaling pathways may reveal new targets for therapies that prevent or stabilize TAA.

Illegal, unreported and unregulated (IUU) fishing violates the rights of Indigenous peoples to traditional fishing grounds; compromises food security of legitimate fishers and coastal populations; and facilitates human labor trafficking. Once caught, tails, fins, and heads are cut off for storage and transportation, which makes identification by phenotype impossible. Polymerase Chain Reaction (PCR) and electrophoresis can detect different tuna species but are time-consuming and require access to a fully equipped laboratory and trained personnel. Thus, I developed a novel biological assay and a 3D printable portable device to detect Ahi tuna, one of the species of interest among three tuna species. The biological assay consists of three steps: DNA extraction by crude lysis method; DNA amplification by Recombinase Polymerase Amplification (RPA); and detection by fluorescence using Clustered Regularly Interspaced Short Palindromic Repeats associated (CRISPR Cas) 12a. qPCR verified Ahi tuna DNA extraction by crude lysis method, generating 10⁶ copies of DNA per reaction comparable to the standard silica-based capture method. Nested qPCR and Tapestation verified RPA’s successful amplification of Ahi tuna DNA extracted by crude lysis method. Quantification of fluorescence by qPCR verified that one-pot RPA and CRISPR Cas12a reactions could generate up to 6000 Relative Fluorescence Units above the negative control within 15 minutes. The isothermal device keeps the samples at a constant temperature (37-42℃) for the RPA and CRISPR Cas12a reactions. I successfully demonstrated a <50 min sample-to-result assay to detect Ahi tuna DNA, and this protocol will be further adapted for testing other types of tuna including Bluefin tuna. By developing such a rapid and affordable isothermal biological assay and a point-of-need 3D printable portable device for tuna identification, I aim to contribute in helping individuals and ecosystems impacted by IUU fishing.

Thoracic aortic aneurysms (TAA) are excessive dilations of the aorta, inside the chest. TAA can rupture, causing sudden death. Human TAA are attributed to both decreased and increased TGF-β signaling in aortic smooth muscle cells (SMC). Experimental data from mice clearly shows that decreased SMC TGF-β signaling causes TAA; however, the connection of increased SMC TGF-β signaling with TAA is largely based on correlational data. Some of these data implicate excessive TGF-β signaling in only one of the two SMC embryonic lineages that populate the proximal thoracic aorta: the cardiac neural crest (CNC) lineage. To directly test whether increased SMC TGF-β signaling in either of the two lineages causes TAA, I am generating mice with increased SMC TGF-β signaling in either CNC-derived or second heart field (SHF)-derived SMC. I accomplish this by using a transgene that expresses a constitutively active TGF-β receptor (TBRI-CA) after activation by Cre recombinase. To express TBRI-CA in CNC-derived SMC, I mate mice with a Wnt1-Cre transgene to mice with the TBRI-CA transgene. To express TBRI-CA in SHF-derived SMC, I mate mice with an Mef2c-Cre transgene to mice with the TBRI-CA transgene. I hope to determine whether increased TGF-β signaling in SMC of either lineage causes TAA. However, because SMC TGF-β signaling plays critical roles in embryonic vascular development, I will begin by determining whether activation of TGF-β signaling in either lineage is embryonically lethal. I am analyzing genotypes of pups from each mating, and using Chi Square or Fisher Exact Test to test the null hypothesis that increased TGF-β signaling in embryonic SMC is not lethal. If my hypothesis is supported, I will then be able to determine whether SMC-targeted activation of TGF-β signaling causes TAA. My findings could provide support for development of human therapies that prevent TAA by blocking SMC TGF-β signaling.

The goal of the SQRLab is to develop technologies for a fully fault tolerant quantum computer capable of processing 10,000 qubits of information. One necessary component is a Paul Trap, consisting of two pairs of blades delivering both direct current (DC) and radio frequency (rf) alternating signals in order to trap and stabilize a string of ions. In order for the modes of the quantum states of these ions to be stable, the stability of power delivery to the device is crucial. Given these design specifications a rf resonator circuit is necessary. The goal of my project is to design, simulate, build, and test a low-loss rf resonator to deliver rf signals to the ion Paul Trap efficiently and stably. Using a toroid shape, I experiment with the material of the wiring and the method of winding the toroid to find a wiring scheme that creates the least loss in delivering power to the experiment. The material used in the wire and dielectric material inside the coil directly affects the efficiency of translating signals. It is desirable that this resonator generates a voltage gain at a specified power level, has impedance matching of the coil with the driving circuit, and contains a method of monitoring this voltage. Thus far, I have measured the voltage gain generated by the coil and the quality factor of the coil (the quality of the resonator frequency as it interacts with the rest of the circuit). I have also designed a capacitive “pickup” to sample the voltage level of the delivered rf power. I will produce noise figures to stabilize the trap power to a set-point voltage level. This research contributes to SQRL’s objective of designing useful scalable quantum systems to simulate nature and perform complex algorithms not permitted by classical computers.

Lignocellulosic biomass, composed of cellulose, hemicellulose, and lignin, has become an attractive renewable carbon source for microbial bioproduction of value-added chemicals. Lignin is relatively difficult to depolymerize, and its enzymatic hydrolysate contains mostly aromatic compounds known to inhibit microbial growth when used as a carbon source. Pseudomonas putida (P. putida), a soil bacteria known for its tolerance to aromatics, has been engineered to catabolize lignin hydrolysate. Engineered microbes have also been encapsulated in hydrogels for on-demand bioproduction and exhibited enhanced tolerance to harsh processing conditions, i.e. freeze-drying and exposure to organic solvents. This research aims to create microbe-laden hydrogels from encapsulating engineered P. putida KT2440 cells in F127-bisurethane methacrylate (F127-BUM) hydrogels for robust on-demand bioproduction when using lignin hydrolysate as a substrate. To mimic growth rate inhibition that often happens in hydrolysate environments, we first examine if P. putida-laden hydrogels remain active when grown in a less-ideal medium, such as M9 minimal media (MM9) known to yield a slower microbial growth rate. We find that hydrogel-encapsulated P. putida containing a plasmid for heterologous expression of a green fluorescent protein (sfGFP) maintained its activity in MM9 continuous culture over two days as measured via fluorescence of the expressed sfGFP. This preliminary result on encapsulated P. putida growth and activity in a less desirable culture environment highlights the potential for utilizing aromatics-rich lignin hydrolysate in bioproduction as a more economical and renewable feedstock alternative.

Wastewater contamination poses a serious threat to global public health. An emerging way that wastewater is treated is through poplar tree evapotranspiration galleries. In this system, microbiomes in the soil can extract pollution out of wastewater. We are conducting controlled studies to evaluate the ability of microbiomes to extract pollutants from secondary wastewater effluent at high water application rates. Our aim is to understand the microbiomes' pollution extraction capacity by studying their composition at varying soil depths with a focus on nitrogen species removal. I collected soil samples from 9 reactors, at two different depths each, and extracted DNA using a Qiagen DNA extraction kit. 16S gene of the DNA will then be sequenced using MinION, MinION is a third-generation sequencing technology with emerging applications for long-read 16S microbiome composition. In parallel, microbiome nitrogen cycling activity will be measured in the lab. The level of nitrogen processing will be compared from the different depths and with comparison to the community composition. We predict that as the depth of the soil increases, the composition of the microbiome will change, and the ability of the microbiome to extract nitrogen pollutants from wastewater decreases. This study will guide the formation of soil around wastewater facilities to optimize pollutant removal from wastewater.

Lung-resident type 1 conventional dendritic cells (cDC1s) are critical for initiating immune responses against foreign respiratory viruses and endogenous assaults like cancer cells. Importantly, the cDCs of each tissue display unique phenotypes and functions dictated by the environment they populate. However, our understanding of the factors that regulate cDC1 development and function in the lung is minimal. The cytokines, FMS-like tyrosine kinase 3 ligand (FLT3L), and granulocyte-macrophage stimulating factor (GM-CSF) are essential for the development of tissue-resident cDC1, but in in vitro systems, these factors are insufficient to generate cDC1s with a lung-specific phenotype. RNAseq analysis of lung cDC1 identified a clear enrichment in genes associated with transforming growth factor beta (TGF-β) signaling, a factor also known to be enriched in the airspaces of the lung. TGF-β has been previously reported to maintain DC quiescence in the lung, however, our data suggested it may also play a role in differentiation and lung specification of these cells. Based on this, I hypothesized that adding TGF-β to in vitro bone marrow (BM) cultures alongside established cytokines FLT3L and GM-CSF would generate cDC1s phenotypically and functionally similar to in vivo lung cDC1s. The addition of TGF-β, but not GM-CSF, to optimized FLT3L-BMDC cultures resulted in development of cDC1 which highly resemble lung cDC1. The development of a high throughput in vitro system that differentiates functional lung cDC1s will not only inform the in vivo factors required for development of these cells but also provides a useful platform for interrogation of lung cDC1 function and a stepping-off point to begin models for human lung cDC1 production and study.

Engineered genetic circuits provide an environmentally friendly path to chemical industries, including fine chemicals and therapeutics. To effectively modulate genetic circuits, a programmable tool to control multiple genes is necessary. CRISPR-mediated gene activation (CRISPRa) is an emerging tool suitable for this purpose. In CRISPRa, a nuclease-deficient dCas9 protein is used to deliver a transcriptional activator domain (MCP-SoxS) upstream of genes of interest. A complementary guide RNA (gRNA) enables dCas9 recruitment to any DNA target. Despite the programmability of CRISPRa, the number of genes that can be simultaneously regulated remain unexplored. In this work, we aim to experimentally investigate the number of gRNAs limitation in the chemical bioproduction context. First, we designed CRISPRa circuits with an increasing number of guide RNAs encoded on plasmids constructed with a scalable and high-throughput technique via Golden Gate Assembly. CRISPRa circuit performance was then evaluated by simultaneously regulating multiple fluorescent proteins as a proxy for multi-enzyme cascade in biosynthetic pathways. Increasing the number of gRNAs was found to decrease CRISPRa activity, suggesting competition of CRISPRa components. Furthermore, we applied the constructed circuits for metabolically engineered pathways in P. putida regulating production of p-aminocinnamic acid (pACA), a precursor for polymer synthesis vital in photovoltaic and biomedical applications. Bioproduction of pACA in P. putida was enabled by simultaneously regulating 9 heterologous genes. The outcome of CRISPRa circuits will be analyzed via High-Performance Liquid Chromatography (HPLC).The implication of this work will allow us to construct large scale CRISPR genetic circuits and optimize multi-gRNA CRISPR circuit integrations into other systems such as non-model organisms and cell-free systems, which will expand metabolic engineering capabilities and chemical productions beneficial in a wide range of biosynthetic applications.

 The primary goal of post-transplant care is to achieve the optimal balance of immunosuppression between infection and rejection. Physicians currently rely on laboratory markers such as changes in serum creatinine. Physicians use kidney allograft biopsies to detect acute rejection but biopsies are expensive, invasive, and susceptible to sampling error. This study investigates the use of donor-derived cell free DNA (dd-cfDNA) as a biomarker for kidney allograft dysfunction to allow for optimization of immunosuppression. This multicenter prospective study (Caredx) examines the correlation between dd-cfDNA levels and infection and rejection episodes in pediatric kidney transplant recipients. Dd-cfDNA is measured 3 to 12 months post-transplant and compared to the clinical outcomes of major infection events and biopsies. Data is collected from November 2019 to 2023 on 59 participants from Seattle Children’s Hospital, St. Louis Children’s Hospital, and Emory University. Using patient’s charts in EPIC I abstract patient demographics, transplant characteristics, laboratory, and kidney biopsy results. I assist with patient recruitment and retention by keeping track of when patients are within sample windows and ensuring their sample requests are sent. Preliminary data from the first 10 samples revealed that elevated dd-cfDNA levels were associated with viral infection or acute rejection episodes. We observed a decrease in the dd-cfDNA levels following treatment for BK viremia. Following data collection, we plan to submit an abstract to the American Society of Nephrology in May of 2023. Additionally, we will prepare a manuscript to submit to the Journal of Pediatric Transplantation in the Summer of 2023. Use of dd-cfDNA will enable early intervention and minimize damage to allografts leading to improved longevity and quality of life. Furthermore, the biomarker is less expensive, less invasive, and more accessible than reliance on transplant biopsies holding the potential to break down economic and physical barriers to health care.

In flowering plants, LEAFY (LFY) is a key floral developmental gene; homologes of LFY exist in nonflowering plants, where this developmental regulatory role cannot exist. In an effort to understand what role LFY serves in a nonflowering plant I am studying the model fern Ceratopteris Richardii, as ferns produce spores not flowers. My goal is to determine if the two fern LFY homologues, CrLFY1/2, play a role in the reproductive or vegetative development of ferns. To investigate this function, I am characterizing the phenotypes of transgenic plants that overexpress one or both of the fern copies. To that end, I record data on key developmental markers across the diploid generation of the fern, or sporophyte. Given that LFY overexpression has been associated with early flowering and leaf compounding in flowering plants, I anticipate early reproductive development and/or abnormal leaf development in my transgenic ferns sporophytes. Preliminary results suggest that transgenic ferns are producing spores earlier than controls, and are not displaying all expected markers of vegetative development. Here, I present data on the vegetative development and appearance of reproductive structures of C. richardii ferns overexpressing one or both of two gene duplicates, CrLFY1 and CrLFY2 to help elucidate the functional evolution of the this important developmental regulator of flowering.

Trapped ions are proving to be a promising realization of quantum computation; computation is performed with an ion — such as 40Ca+ — contained by an electric potential and irradiated with laser beams of multiple wavelengths for ion cooling and qubit state control. Advantages to other implementations include repeatability and efficiency in state preparation, gate operation, and state readout. However, a number of ions are required for useful operation, and larger systems introduce complexity and possibility for error, which necessitates modular and scalable trap geometries fabricated using common methods pioneered by the semiconductor industry. Two-dimensional surface traps can suffer from low trapping depth, low efficiency, and higher ion motion, complicating high-fidelity operation. We explore alternative geometries, such as traps with multiple surfaces, and elucidate acceptable misalignment or non-ideal geometries. Our method exploits a multipole expansion of electric potentials produced through COMSOL; we expect to use the resulting multipole coefficients, trap depth, and trap frequency to inform fabrication tolerances and parameters such as electrode spacing, size, or shape. Through proper fabrication and optimal design informed by this work, traps with high depth, high efficiency, and low ion motion can aid the push for modular trapped-ion quantum computing.

In the era of Internet of Things, the operation of various kinds of sensors or devices on the shelves in warehouses or supermarkets often requires batteries or complex wire management. To address this issue, we propose a charging solution utilizing the near-field wireless power transfer (WPT) with multiple relay resonators, also known as a multi-hop WPT system. In this study, we designed and simulated several coil geometries for the WPT system to ensure high efficient power can be delivered from a transmitter to a receiver through various coil hopping configurations. After evaluating the trade-off between the coupling coefficient of coils in parallel and series as well as the design complexities, we constructed many unified coils in one geometry. We then measured the coil-to-coil estimated efficiency using the scattering parameter obtained through a Vector Network Analyzer on a foam board shelf. Our results show the efficiency range from 9% to 81% in the worst and best hopping configurations, respectively. Furthermore, we proposed a power efficiency optimization approach to improve the worst hopping configuration by up to 80%. We anticipate that the success of this work will significantly reduce the staff cost associated with the maintenance of wire management and charging systems on each shelf. It will also simplify the assembly process and enhance the accessibility of smart shelves while potentially mitigating environmental impact by reducing battery usage.

In this research project, our multidisciplinary team is developing environmental forensic technology to identify illegally caught seafood, with a focus on high-value species such as bluefin tuna. To tackle the difficult task of immediately detecting illegal, unregulated, and unreported (IUU) fishing, we are developing a rapid, affordable, and portable detection device that uses isothermal amplification and blue LEDs to detect resultant green fluorescent products indicating the presence of tuna DNA. As the lead Electrical Engineer, I designed an electrical circuit to precisely and stably control the temperature of a resistive heater using a microcontroller, thermistor, and PID algorithm along with an LED circuit. The requirement for the process involves the utilization of isothermal amplification technique at a fixed temperature of 37°C (33-42°C range) and green fluorescence detection (at 550 nm) in DNA using blue LEDs (at 470 nm) and an orange acrylic filter to filter the blue wavelength. The result is a circuit that meets the requirements for the biochemical process and enables real-time feedback without the need for shipping samples to a laboratory. With the development of the device finished, the next step is to streamline the user experience. I am leading the software development effort to create a phone application that facilitates the assay setup process and automates image capturing and analysis. With a capable research team, including colleagues shaping the user interface, a junior researcher connecting the device to the phone application, and a Ph.D. candidate in Computer Science and Engineering developing a proprietary camera software, our team's effort culminates in a user-friendly phone app that streamlines the assay workflow and provides real-time sample analysis. With the completion of this project, we will be able to make a difference by helping communities and marine ecosystems.

River otters (Lontara canadensis) are high trophic level opportunistic feeders. Their diet, examined through scat, provides key information about local ecosystems. Previous studies have observed a diet dominated by fish, including studies in California (90%), Utah (96.5%), and North Dakota (83%); however, my preliminary results on otter diet at the mouth of the Snohomish River highlight a greater variation in observed prey. The meeting of the Snohomish River and Possession Sound creates a salt wedge estuary with extensive tide flats, providing access to diverse freshwater and saltwater prey species. From 2012-2015, river otter scat samples were collected, dissected, and identified by students at the Ocean Research College Academy (ORCA). Averages over the three years showed that fish were the dominant prey type in fall, winter, and summer; however, crustaceans dominated the river otter diet in the spring. In this study, I dissected scat samples from fall 2022 through spring 2023 from 2 sample locations in Everett Marina. In the more recent data, fall 2022 has followed the pattern of these historical studies, but the winter samples have indicated a shift of fish and crustaceans. In fall 2022, 5/25 samples showed 50% or fewer fish bones, while winter 2023 showed 11/13 samples with less than 50% fish bones. Given that otters are described as opportunistic feeders, this shift in winter diet, relative to previous years, may suggest a significant environmental shift. Future research must examine physical environmental features such as changes in river discharge and/or water temperature. Identifying specific fish species in samples may also reveal prey availability throughout the seasons.

Phytoplankton production depends on a number of factors including nutrient availability, water chemistry variables, and light penetration. Previous studies have shown light penetration to be important for submerged aquatic vegetation, the primary producers that support the marine food web and the ecosystem. Possession Sound is a productive sub-basin of the Salish Sea with complex influences on local water chemistry and primary productivity. Given the significance of primary production in a salt water estuary, this study looks at the seasonal relationships between water chemistry and light penetration, measured by photosynthetically active radiation (PAR) in the Possession Sound estuary across three sites. I collected Seabird CTD and YSI EXO profile data as well as PAR sensor results, in Possession Sound from July 2022 through March 2023. Accompanied with historical data collected by past Ocean Research College Academy researchers, I analyzed site dependent relationships as well as the seasonal relationships. Preliminary analyses showed PAR decreasing with higher salinity and turbidity, but increasing with temperature. Limited connection was observed with dissolved oxygen. Studying the relationships among light penetration and water chemistry allows us to better understand the complex relationships among the key factors determining seasonal primary production.

Indium phosphide (InP) magic-size clusters (MSCs) are atomically-precise molecules that can be used as precursors to quantum dots (QDs). In a reaction to form InP MSCs, QDs are the thermodynamic product, whereas MSCs are a kinetic product, so there is a critical temperature below which a reaction will form MSCs but above which a reaction will form QDs. The goal of this project is to explore the effect of ligand identity on the formation and stabilization of InP MSCs and their subsequent conversion to QDs. For carboxylates, which bind weakly to InP surfaces, the critical temperature is about 120 ËšC. For phosphonic acids, which bind strongly to InP surfaces this temperature is so high that cannot be reached via a heating mantle – above about 400 ËšC. I am working to investigate the effects of native thiols/thiolate ligands on the synthesis of InP MSCs. Thiols are intermediate in their binding strength to and are commonly used with InP surfaces. I will probe the concentrations and temperatures at which thiolate-capped InP MSCs form. I hypothesize that the critical temperature for the synthesis of MSCs versus QDs reflects the ligand binding strength. If this is true, thiolate-capped InP MSCs should form readily at temperatures above 120 ËšC, but the temperature at which QDs are formed should be achievable via a heating mantle, opening up new parameter space for QD and cluster synthesis and study.

Metal–organic frameworks (MOFs) are a class of crystalline, porous extended solids that are formed through coordination between metal cations and bridging organic ligands. These materials have been a topic of acute interest in the scientific community due to their intrinsic porosity, high surface area, and precise tunability. However, MOFs are typically insulating, which limits the scope of their applications. The recent development of electrically conductive MOFs has opened the door to exciting multifunctional applications in electrocatalysis, advanced electrochemical energy storage, chemical sensing, and much more. However, a molecular-level understanding of charge transport in MOFs remains lacking. My research aims to address this knowledge gap through the investigation of one-dimensional (1D) metal–organic chains. In this presentation, I will introduce the synthesis of a series of highly-tunable 1D metal–organic chains that exhibit delocalized π systems and high electrical conductivity along with studies of how structural parameters such as metal/ligand identity and chain geometry influence their overall electrical and magnetic properties. My preliminary results demonstrate trends in these structure-property relationships that may inform how these materials can be rationally designed with specific magnetic and conductive properties. Ultimately, this work will contribute towards a molecular-level understanding of charge transport and magnetism in metal–organic frameworks, enabling the design of new conductive porous materials that can use electricity to drive chemical processes.

Lacking in early emotional support has been associated with emotional dysregulation and impulsivity in adulthood. Although previous research has also demonstrated that emotion dysregulation and impulsivity are both crucial factors associated to alcohol-related problems, to our knowledge there is no study exploring the relationship between early emotional support and alcohol use in adulthood through the mechanisms of emotion dysregulation and urgency. Additionally, previous work has mostly relied on cross-sectional data. The current study aims to explore the association between early emotional support and alcohol use by assessing the role of emotion dysregulation and urgency as mediators. We use pilot data collected via cross-sectional and ecological momentary assessment (EMA) methodology. Emotion dysregulation will be assessed by the Cognitive Emotion Regulation Questionnaire (CERQ; Garnefski & Kraaij, 2001). Urgency was assessed by the averaged values of the negative and positive urgency subscales in the 59-item Impulsive Behavior Scale (UPPS-P; Whiteside & Lynam, 2001; Lynam, Smith, Whiteside, & Cyders, 2006). Early emotional support was assessed by the emotional support subscale in the Multidimensional Neglect Behavior Scale (Dubowitz et al., 2011). Alcohol use was assessed by the Daily Drinking Questionnaire (DDQ-R; Collins, Parks, & Marlatt, 1985). Longitudinal items were gathered from a subset of the above measures. For the purposes of this presentation, we plan to analyze the data using bivariate correlation analyses in preparation for a full mediation analysis in the full study. We expect to find that those lacking in emotional support during adolescence predicts both emotional dysregulation and urgency in adulthood, which leading to alcohol-related problems in adulthood. Results in the expected directions would suggest that low emotional support in adolescence may be a risk factor for substance abuse later in life, showcasing a need for caregivers to better the emotional states of their children.

Many standard oxidants and reductants are non-reusable and toxic, so it is important to pursue cleaner alternatives. In this project, we have synthesized and characterized two metal-bipyridyl supramolecular cages and have studied their application as catalysts for the electrochemical reduction of organic substrates. Supramolecular cages are formed from the self-assembly of organic ligands and metal ions in solution, and they contain internal cavities with unique electronic microenvironments, similar to the interior of enzymes. While these polyhedral structures have been investigated as catalysts for traditional synthetic pathways, their role in electrosynthesis remains underexplored. Electrosynthesis involves the transfer of electrons to and from substrates using an applied potential, rather than chemical redox agents. This method is often hindered by a high kinetic barrier at the electrode-substrate interface, but catalysts can lower this barrier. We hypothesize that redox-active supramolecular cages – cages that can readily interconvert between charge states – can serve as effective electrocatalysts by encapsulating and transferring charge to substrates. To understand the effect of ligand geometry on electrocatalysis, I have synthesized two redox-active ligands with bipyridyl chelating groups. One contains a highly conjugated perylene core, while the other contains a compact core formed from pyromellitic dianhydride. We have metalated these ligands with iron ions to form two tetrahedral supramolecular cages. We then utilized cyclic voltammetry to assess cage-facilitated charge transfer to vicinal dihalide substrates. We observed that the reduction of multiple substrates, including 1,2-dibromo-1,2-diphenylethane, occurred at milder voltages in the presence of the cages, indicating a reduced kinetic barrier. For these substrates, we then performed bulk electrolysis, from which we determined that the percent conversion to the desired product was significantly higher when a cage was present, supporting our hypothesis. Ultimately, we aim to use these cages to enable electrosynthesis of organic feedstocks at lower voltages and with fewer byproducts.

Previous work takes inspiration from 2D metal–organic frameworks to synthesize 0D metal–organic macrocycles which maintain the conductivity of the original material while introducing solution processability. These macrocycles self-assemble into nanotubes through π-π stacking of the aromatic core but, the nanotubes do not have a preferred orientation when imaged by atomic force microscopy (AFM). We hypothesize that by adjusting solvent, drying conditions, and organic ligand functionality we can create a preferred orientation of the macrocycle nanotubes on common substrates which will improve charge carrier mobilities through the aromatic core. This work demonstrates the formation of large domains of nanotube alignment which can lead to greater charge carrier mobility. With unique ambipolar charge carrier transport, metal–organic macrocycles have applications in energy storage, chemical sensing, and electrocatalysis.

Mobility models, which stimulates movement patterns of individuals or groups, play pivotal roles in assisting urban planning, transportation, and public health. As these mobility models are progressively used to create new government policies and allocate resources in cities, it is crucial to consider the impact of amplifying or perpetuating existing biases or unfairness. Currently, the existing research is aimed at generating synthetic traces from real historical data and protecting the privacy of traces, but rarely on the fairness dimension of these mobility traces. This research specifically investigates the fairness dimension of mobility models. The fairness will be determined by analyzing the Common Part of Commuters (CPC) for different sensitive groups. CPC is the metric that is used in measuring how accurate the synthetic traces are compared to the real data. The different sensitive groups will be created by grouping the extremities of CDC’s Social Vulnerability Index (SVI), which considers a range of factors including socioeconomic status, household composition, race/ethnicity/language, and housing/transportation. The research will result in a package extension that will allow all users to analyze for fairness in Mobility Models between the wealthy and less privileged regions. We anticipate that mobility models will have a higher average and higher distribution of CPC in the more privileged regions.

In face-to-face surveys containing sensitive questions, Social Desirability Bias (SDB), respondent’s tendency to provide socially acceptable responses rather than truthful ones, can compromise data accuracy. Randomized response techniques (RRT) are survey models that allow respondents to provide scrambled responses, thereby circumventing SDB. In this study, we introduce a mixture optional quantitative RRT model that combines the elements of both the Pollock and Bek (1976) additive RRT model and the Greenberg et al. (1971) unrelated question quantitative RRT model. We examine the utility of the proposed mixture model using a unified measure of efficiency and privacy introduced by Gupta et al. (2018) that provides a metric of both predictive accuracy and respondent privacy. We also account for the lack of trust in RRT models. Both empirical and theoretical results show that the mixture model outperforms the two component models. The proposed optional quantitative mixture RRT model provides a survey technique that can account for not only SDB but also respondent lack of trust, leading to more accurate and interpretable data used to inform decision making that does not compromise the privacy of respondents.

Nostalgic contents are social media posts that refer to past collective memories or events. When crisis events do occur, it affects the way of living life. In these unprecedented times, people turn to social media to express their concerns and feelings. By studying the engagement and interactions of users in social media, we can create new ways of understanding nostalgic longing. This research explores the nostalgic activity of tweets during crisis events. The NLP (Natural Language Processing) classifier is a pre-trained algorithm that enables us to detect whether the tweet is nostalgic or not by using references to human language and then classifying them into categories. The performance of our classifier is 98% accurate. This accuracy ensures the detection of nostalgic tweets is correct when formulating an analysis. Once the nostalgic tweets are obtained from the classifier I can begin performing a deeper analysis of the tweets by using machine learning tools. A descriptive analysis of time is used to gain insight into how people react to events and the progression of the nostalgia feeling humans have. Especially pre-crisis, during a crisis, and post-crisis are time periods that are significant because it gives insight into the progression of human behavior. Sentiment analysis is also performed on the data to understand how people feel about certain events. This is a useful method to gain information about whether there is a positive or negative reminiscent during the time the tweet is posted. The analysis has shown that less than 1% of tweets are nostalgic and the contents tend to be more negative than positive. The content of the tweets ranges from informational to political with a reminiscent of the time during crisis. The results will help us understand human behavior and how it can be leveraged as public assistance during a crisis.

The "Missing Maps" research project targets remote secluded communities across large regions of the globe. In this project, we train a model that leverages satellite images to find settlements, houses, and villages so that humanitarian organizations and community health systems can know about every community in the area. This has a high impact and helps non-governmental organization and local policymakers to meet the needs of people in rural areas and plan relief efforts in cases of crisis or natural disasters. There is extensive research on training neural networks to recognize buildings on satellite images for big cities like New York or Las Vegas, but not on rural satellite images to identify remote communities. In the "Missing Maps" research project, we use ensemble methods that combine multiple machine learning models to solve the problem holistically and improve accuracy as a result while adapting it to a diverse variety of continents and areas. Some of the methods explored in this research are based on community detection using neural networks and advanced image inpainting. The models are trained using the latest datasets, such as OpenEarthMaps and OpenBuildings. This project diversifies satellite image analysis and addresses the biases in algorithms that are only targeting urban areas.

The modern education system has the opportunity to raise students with a well-rounded, interdisciplinary knowledge base, but that does not begin until textbooks (the backbone of many science curricula) include such topics. We wondered to what extent Multiple Ways of Knowing (MWoK), particularly in the topics of religion, culture, traditional medicine, and philosophy, are represented in introductory biology textbooks. The term MWoK describes these topics and recognizes that there is more than one way to learn and understand, crediting different cultures for their scientific contributions. This study is a spin-off from a greater project in which our team scored and evaluated six introductory biology textbooks on how much and how well they included a variety of social justice topics. Using the data gathered from the aforementioned study, we categorized the instances of MWoK by frequently occuring themes - religion, culture, traditional medicine, and other. We found that across over 9670 pages, these textbooks lack adequate discussion of MWoK, with only 32 mentions. Within these few instances, only one showed themes of justice or injustice, and one demonstrated themes of equity and inequity. Textbooks alone are insufficient for implementing the diversity of science in American classrooms. We envision this research as a starting point for instructors to integrate these topics into their classes. Incorporating more involved conversations about MWoK within the context of science can act as a way to foster a more inclusive learning environment wherein all students are able to engage more meaningfully with the material. Including MWoK in biology textbooks, and thus, biology curricula, would bring the STEM classroom one step closer towards increased diversity. 

Research, and evolutionary theory, demonstrates that romantic relationships and platonic friendships fulfill different needs and are necessary for survival and critical for reproductive success. These relationships can be highly gendered with different dynamics. Usually, women’s same and cross-sex friendships are more fulfilling and richer. However, there is limited research looking at romantic relationships and platonic friendships and the individual differences and characteristics within these relationships. The current research explores how gender, sexuality, and heteronormativity impact the assessment, comparison, and characteristics between platonic and romantic relationships. We explore which individuals break out of traditional gendered friendship norms and seek similar interactions within their platonic friendships and romantic relationships. 194 Participants answered a questionnaire measuring the different characteristics desired in platonic friendships and romantic relationships. This survey was answered twice, once while thinking about a platonic friend and again for a romantic partner. Relationship characteristics were measured by scales, created by the researchers, that looked at emotional intimacy, physical intimacy, quality time, action affection, verbal assurance, and relationship perception. Romantic relationships had no difference between genders or sexualities for any of the scales. However, there were significant differences between genders and sexualities found in platonic relationships. Non-heterosexual women and non-binary individuals had higher engagement and support and had the highest overall assessment ratings within their platonic relationships. Heterosexual men and non-heterosexual women differed the most in their ratings for all platonic relationship characteristics, heterosexual men having lower scores on average. This supports previous research that men have less fulfilling relationships than women.

Postpartum depression (PPD), with prevalence rates in East Africa ranging from 17% to 24%, is associated with adverse health outcomes among offspring of affected mothers including emotional and developmental delays and poor growth. The 2022 World Health Organization (WHO) maternal and newborn care recommendations call for routine PPD screening using a validated screening tool. In Rwanda, a low-income country severely impacted by the 1994 genocide, routine PPD screening has not been implemented. This study was conducted to describe the prevalence of PPD among new mothers and determine sociodemographic characteristics and health factors associated with PPD and recent suicidal ideation. Postpartum mothers delivering a live birth at the Kabutare District Hospital (KDH) in Huye, Rwanda between August and September 2022 were recruited for this study. This study was a cross-sectional survey administered via face-to-face interviews conducted in Kinyarwanda. Following written consent, the mothers responded to sociodemographic, and maternal/ infant health questions, and completed the Edinburgh Postnatal Depression Scale (EPDS). Postpartum depression was defined as an EPDS score of > 10. Data collection was approved by the KDH Ethics Committee. Our study population consisted of 66 Kinyarwanda-speaking mothers. Over half (52%) had PPD, and 26% had suicidal thoughts in the past 7 days. Many reported a history of depression (39%), PPD (18%), or anxiety (29%). Mothers with a history of depression, anxiety, or PPD were more likely to have PPD and recent suicidal ideation. There was a greater prevalence of PPD among mothers reporting pregnancy-related complications or a history of mental illness compared to their counterparts (70% vs. 44%, p < 0.05; 67% vs. 36%, p < 0.05). Mothers at particularly high risk for PPD are those with pregnancy-related complications and a history of mental illness. These findings demonstrate a need for routine PPD screening among new mothers, as recommended by WHO.

Neutrinos are fundamental particles involved in many important universal processes; however, because they only interact via the weak force and gravity, reliably detecting neutrinos directly is notoriously difficult. A new strategy is to study neutrinos through interactions with enhanced cross-section, like coherent elastic neutrino-nucleus scattering (CEvNS), in which the neutrino interacts with the nucleus as a whole (coherent) while conserving kinetic energy (elastic). However, due to the low energy of nuclear recoil in CEvNS, not all nuclei can produce detectable recoil if the recoil energy is on the order of the noise fluctuations in other background radiative processes, as recoil energies become indiscernible. Sodium iodide (NaI) is a candidate for detectable recoil, and I am characterizing the background spectrum of NaI crystals to see if NaI has low enough rates of background processes to be used in CEvNS studies. I analyzed previously collected NaI background spectra to calibrate the event energies and to perform a waveform analysis to distinguish physics pulses from electronics noise. The resulting spectra are used to determine the background rates in the crystals. These routines were converted into scripts to automate the same analysis for future data. Measuring the energy of CEvNS nuclear recoil can help characterize neutrino-quark interactions, which the coherent nature of CEvNS amplifies, providing unprecedented sensitivity to searches for non-standard interactions between neutrinos and matter. Improved characterization of CEvNS also allows for novel checks of predictions made by the Standard Model of particle physics, and has broader applications in understanding supernovae (which produce large quantities of neutrinos) and searches of dark matter candidates that may interact with neutrinos.

Particle-laden turbulent flows are important in both natural and industrial contexts. The particles in many of these processes, such as the formation of ice crystals in clouds or the paper-making process, are anisotropic, with directionally-dependent drag coefficients. Generally, anisotropic particles are free to rotate as they are advected by the carrier fluid. However, external forcing from gravitational and magnetic fields, the larger scale flow, and active behavior can restrict the particles’ orientation, fixing their anisotropic resistance with respect to the reference frame. The dynamics and statistics of symmetric particles in isotropic turbulence are well-studied, but the effect of anisotropic forcing on the transport and behavior of asymmetric particles is less well-understood. We studied these dynamics by conducting Lagrangian particle tracking in simulated isotropic turbulence from the Johns Hopkins Turbulence Database. Computer simulations of 54,000 randomly-placed particle tracers were run in Python, with anisotropy introduced by directly scaling the velocity of the tracer-particle at each simulation time step. We examine how increasing a particle’s resistance to motion in one direction in isotropic turbulence impacts the transport and dispersion statistics in all three directions. We find that increasing tracer anisotropy decreases diffusivity in the direction of velocity scaling as expected, but the diffusivity in the unscaled directions increases such that the total diffusivity remains roughly constant. Studying the dynamics of these simulated anisotropic particles in turbulence will provide a better understanding of how turbulence mixes both particles and the fluid itself, which can then be applied to particle-turbulence interactions in both environmental and industrial contexts.