Plasma, a fluid consisting of highly charged particles, is the single most abundant state of matter in the universe, yet our understanding of its properties remains incomplete. One common method of generating plasma is by inducing a large voltage difference between two charged electrodes in a low-pressure environment, referred to as direct current (DC) plasma. Understanding the relationship between plasma temperature and spectral line intensity as a function of external parameters, such as voltage, pressure, and position, is crucial to optimizing plasma-based processes. This study analyzes these dependencies systematically to help build a further understanding of the spatially dependent properties of DC plasmas. We extract electron temperature from spectroscopic measurements by analyzing line intensities assuming a Maxwell-Boltzmann electron energy distribution. The intensity of spectral lines is related to electron energy via the Boltzmann factor, allowing for temperature determination through a logarithmic plot of intensity ratios versus upper energy levels. By varying voltage and pressure, we identified trends in intensity and temperature, providing insights into plasma behavior. Our results suggest that higher discharge voltages correspond to an increase in electron temperatures, indicating a direct relationship between voltage and temperature. These results provide a greater understanding of plasma-based processes, paving a path toward greater efficiency in applications such as semiconductor manufacturing, surface treatment, and materials processing.

Sound is a vibration that is created by an oscillating object and travels in periodic waves of pressure through a medium. Sound waves are characterized by properties such as frequency, amplitude, wavelength, and speed. The purpose of my research was to measure the effects the lower temperature and air pressure present in the stratosphere have on the properties of sound. To conduct this research I custom-designed an Arduino based sensor with a barometer and thermometer that was then attached to a weather balloon. The sensor also had a buzzer that repeated a tone at constant intervals along with a microphone that measured the amplitude of sound across various frequencies as it was necessary to consider the impact that the high wind speeds present in the stratosphere would have on the measurements. As the air becomes colder and less dense it also becomes less elastic causing it to transfer energy less efficiently which in turn leads to a decrease in amplitude. Frequency, however, did not change as it is determined by the source of the sound and does not depend on the properties of the medium. Understanding how changes in the properties of the medium affect the properties of sound opens a path to using sound to illuminate the properties of the medium. Additionally, broadening our understanding of how various atmospheric conditions present on our own planet affect the properties of sound deepens our understanding of how the various atmospheric conditions present on other planets will impact the properties of sound.

Adoptive cell therapy with CAR-T cells has shown promise in hematological malignancies, but efficacy in solid tumors remains a challenge in part due to CAR-T cell exhaustion and antigen heterogeneity. However, the vast majority of preclinical models do not recapitulate the tumor-immune interactions that produce these barriers. To study CAR-T therapy in a rigorous model that recapitulates tumor-immune barriers, we adapted a Kras^LSL-G12D/+;P53^f/f (KP) genetically engineered mouse model (GEMM) of lung adenocarcinoma. However, adapting the KP-GEMM model for various target antigens, genetic drivers of disease, or interfacing with the vast array of powerful genetic mouse models is resource intensive which prohibits widespread utility. Here, we propose a defined, modular system for generating GEMM for CAR-T preclinical studies using the Sleeping Beauty (SB) transposon system. The proposed system uses polyethylenimine (PEI) to deliver SB transposon encoding oncogenic Kras^G12D and P53^R175H dominant alleles as well as our target antigen hROR1, in vivo to wild-type mice. We demonstrate that in vitro PEI successfully introduces genetic cargo into lung epithelial cell lines, while SB transposons mediate stable integration and expression. Next, we will test this in vivo. This system affords the induction of tumors with specific oncogenic driver mutations and specific tumor antigens on any genetic background. Ultimately, we expect that this approach will streamline preclinical use of GEMM in preclinical research. 

Previous studies have established that galaxy shape and structure, otherwise known as morphology, correlate with environmental density: elliptical galaxies are more prevalent in high-density regions, and spiral galaxies are more prevalent in low-density environments. However, recent studies suggest that stellar mass may primarily drive this trend. In this work, we analyze around 3 million galaxies observed by the Hyper Suprime-Cam survey to reassess the correlation of morphology with large-scale environmental density from a quantitative perspective. The morphological measurements for our galaxies were done using the Bayesian machine learning framework Galaxy Morphology Posterior Estimation Network (GaMPEN). Our analysis employs a Monte Carlo-based framework to account for uncertainties in structural parameter measurements while investigating the correlation between bulge-to-total light ratio, the proportion of light emitted from the center of a galaxy, and environmental density. Leveraging the statistical power of our large dataset, we conclusively demonstrate that the morphology-environment correlation disappears when controlling for stellar mass. Thus, the observed trend arises predominantly because denser environments preferentially host more massive galaxies, making stellar mass the key driver of the morphology-environment relationship. Our results mark a significant advance in addressing this long-standing debate. Furthermore, the methodological framework presented provides a versatile tool for probing the interplay between galaxy properties and the large-scale structure of the universe, which will be particularly valuable in light of ongoing and forthcoming large surveys that supply high-resolution data needed to examine this relationship across extensive cosmic volumes.

The Democratic Republic of Congo (DRC) owns abundant natural resources like minerals and oil, yet they struggle to translate this wealth into sustainable economic growth and prosperity. This research explores the question: What strategies can the DRC implement to achieve sustainable economic growth while fostering prosperity for its population? The study hypothesizes that embracing resource-driven economic diversification, improved governance, and international partnerships can transform the DRC’s economic trajectory. This research is a secondary research because there are many study cases for many countries in which they had faced economic challenges due to the non-transparency of their government. One example is Brazil; they are also land-rich and rich in natural resources. However, unlike the DRC, Brazil has managed to achieve a significantly higher GDP. This research indicates that a major factor behind the DRC’s hardship is the lack of transparency in its government, which reduces foreign investor confidence and limits economic growth. To foster their prosperity, we suggest that global organizations, like the International Monetary Fund (IMF), communicate with the DRC’s government based on the information from the World Bank and IMF for their openness to trade and transparent management to confide foreign investors’ investment in the country. If these, transparent government and confiding foreign investors strategies are well-implemented, this project could greatly impact many nations. It could lift millions of people out of economic hardship and turn the DRC into an example for other nations with similar challenges, especially in the African continent. The accomplishments made by the transparent government and confiding foreign investors policy in DRC may act as a model for nations worldwide on how to develop an economy that is sustainable, equitable, and advantageous for every world citizen.

Magnetic field models of the Earth used for scientific applications and navigation systems are often mapped using ground and satellite measurements, but are rarely done at high altitudes in the atmosphere. Including magnetic field measurements from the upper troposphere and stratosphere could better inform these models. For this study, we used a MLX90393 magnetic field sensor to measure the magnetic field during a high altitude balloon flight. The sensor has a range of -20°C to 85°C, but temperatures often reach -50°C in the upper troposphere and lower stratosphere. In an attempt to keep the sensor within its operating range, we built an insulated enclosure of Styrofoam and mylar. The enclosure was sealed with weather resistant silicone and chemical hand warmers were placed inside. To improve the accuracy of magnetic field measurements on future balloon flights, we compared magnetic field measurements from a non-insulated and an insulated sensor during a high altitude balloon flight. In addition to magnetic field measurements, temperature and pressure measurements were taken inside and outside of the enclosure using a BMP-180 sensor.

Climate change has affected every part of the world. However, nowhere is affected more than the Arctic. More and more arctic ice melts every season, and while the environmental implications are disastrous, it may open up positive new opportunities for trade and recreation, bringing life into small, dwindling Arctic economies. One area of the Arctic that will see increased use in the future is the Northwest Passage (NWP). The once icelocked and barely usable trade route has the potential to influence the economy of all territories it touches, primarily Alaska. Current data indicates that the melting ice along the NWP will have a positive impact on the Alaskan economy. This Literature Review predicts the possible quantitative impact on the region. Strategically positioned Alaskan communities, such as Nome, have fragile infrastructures which will have to adapt to increased commercial demand from cruise ships and recreational vessels. While it is unlikely that trade will have much of an impact economically as most of the ships will not stop along the route, it is likely that the increase in cruise ships will stimulate forced economic and infrastructural growth for these communities. Additionally, as this region of Alaska is mostly undisturbed, there needs to be more study into the environmental impacts of economic growth in the area. Considering the possibility of the NWP becoming a well traveled route is essential in order to help prepare small towns for potential economic booms. An overview of the research suggests that while trade in general may not impact the overall Alaskan economy, the potential increase in tourism via cruise ships and other recreational vessels has the potential to overwhelm the infrastructure of smaller Alaskan cities, even as it jump-starts their economies.

Pseudomonas aeruginosa (Pa) is an opportunistic pathogen that infects the airways of people with cystic fibrosis, a genetic disease that increases susceptibility to lung infections. Pa uses an intercellular communication system called quorum sensing (QS) that allows bacteria to sense cell density and coordinate behaviors among the population, including regulation of virulence. In the laboratory strain PAO1, there are three complete QS systems in Pa that are regulated by the transcription factors LasR, RhlR, and PqsR. PAO1 QS is organized hierarchically with LasR regulating RhlR, and the hierarchy is influenced by the transcription factor MexT that delays RhlR activity. However, it is unknown if QS hierarchy is found widely in Pa strains. My project tested whether the QS hierarchy exists in clinical isolates of Pa. We obtained 3 clinical isolates with intact lasR, rhlR, and mexT genes and created lasR and mexT knockout mutants for each strain to test the effects on RhlR activity compared to wild-type. To measure RhlR activity, we transformed each strain with a RhlR reporter plasmid. We found that a PAO1 mexT mutant shows greater RhlR activity compared to wild-type, while each clinical isolate showed similar RhlR activity between wild-type and the mexT mutant. We observed lower RhlR activity in clinical-isolate lasR mutants compared to wild-type, demonstrating LasR-dependent QS like PAO1. In PAO1, a ∆lasR∆mexT double knockout mutant restored RhlR activity. Interestingly, in clinical isolates, we observed no change in RhlR activity in these ∆lasR∆mexT double knockout mutants as compared to the lasR mutant, indicating MexT is not regulating QS hierarchy in these clinical isolates. Altogether, the clinical isolates displayed a LasR-dependent QS architecture similar to PAO1, but this was not dependent on MexT. Thus, my work points to undiscovered factors that influence QS architecture and highlight the diversity of QS regulation in strains of Pa.

The resistance of castration-resistant prostate cancer (CRPC) to androgen receptor signaling inhibitors (ARSIs) continues to be a significant clinical problem. Translation inhibitors are being researched as a potential treatment for AR-independent CRPC after our laboratory discovered that elevated mRNA translation as one of the major contributing factors. We screened pharmaceutical firms' known mRNA translation inhibitors in three human LuCaP models of advanced prostate cancer: AR-low prostate cancer (LuCaP 176), castration-resistant prostate cancer (LuCaP 35CR), and AR-intact castration-sensitive prostate cancer (LuCaP 35CS). We discovered that only a unique eukaryotic translation initiation factor 4E (eIF4E) 5' cap-binding domain inhibitor was able to efficiently target LuCaP 176, whereas the majority of inhibitors were able to stop the growth of LuCaP 35CS/CR. 5' cap binding inhibition increased the efficacy of enzalutamide in AR-low cells by inducing basal to luminal lineage plasticity and post-transcriptionally downregulating basal keratins. Furthermore, in the AR-low basal LuCaP 176 PDX (patient derived xenograft) model, enzalutamide effectiveness was enhanced by eIF4E cap binding domain suppression. These results are consistent with patient data indicating that people with elevated eIF4E levels have faster resistance to ARSI. Overall, our preliminary data demonstrates that translation inhibitors targeting the eIF4E cap binding domain can reverse lineage plasticity through a translation-based mechanism and sensitize AR-low prostate cancers to ARSIs. To further investigate these mechanisms and assess their implications in patient specimens, we are determining how eIF4E cap binding domain inhibition regulates translation of basal keratins and cellular plasticity along with impacting CRPC growth. Our study shows a promising method for reducing ARSI resistance in deadly metastatic CRPC which is to target eIF4E cap-binding. In order to optimize patient outcomes, this study lays the groundwork for eIF4E cap binding domain inhibition as a possible therapeutic and incorporates a cap-binding assay as a biomarker for individualized treatment.

Tame knots, which are equivalent to a polygonal knot with a finite number of sides, have well-studied invariants; conversely, wild knots that exhibit infinite and pathological behavior are difficult to study and classify. Knot mosaics, introduced by Lomanoco and Kauffman, are an example of a complete invariant for tame knots. Our project aims to expand the existing formal system of knot mosaics to develop an invariant for wild knots. We define n-singular mosaic tangles, the mosaic analog of tangle insertions in pseudoknots and singular knots, and we formalize a system of infinite insertion that generates a wild mosaic to represent certain wild knots. We also intend to define wild mosaic equivalence moves to capture the notion of wild knot equivalence in the mosaic setting. This gives insight to many wild knots explored in existing literature and provides methods to generate and classify new examples.

Sequencing of deoxyribonucleic acid (DNA) is important for a variety of biological and medical research. Nanopore sequencing is a fast and effective way to sequence DNA, and can be used for DNA with genetic alphabets that go beyond the four naturally occurring nucleobases (adenine, guanine, cytosine, thymine). Our group has used nanopore sequencing on synthesized eight-letter “hachimoji” DNA, which contains four artificial nucleotides (called P, Z, S, and B) in addition to the four nucleotides of natural DNA. Expanding sequencing efforts is critical in furthering biotechnological applications of such artificial DNA. Nanopore sequencing requires a motor enzyme to control the translocation of the DNA through the pore. Here, I analyzed the interactions between the Hel308 helicase and hachimoji DNA, specifically the time that Hel308 spends at a step along the DNA (known as the dwell time) and the tendency for Hel308 to step backwards (known as the back step probability). I compared my results to previous work done by our group using natural DNA, and found sequence-dependent behavior at similar sites in the enzyme for both the natural and artificial nucleotides. Studying the kinetics of Hel308 offers deeper insight into its mechanisms and role in genetic processes, as well as its use for other bioengineering applications.