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PHYS2025CHIARELLI7742 PHYS

Interplay of syncytia and antibodies during viral infections

Type: Undergraduate
Author(s): Aubrey Chiarelli Physics & Astronomy
Advisor(s): Hana Dobrovolny Physics & Astronomy

Several viruses can cause cells to fuse into large multinucleated cells called syncytia. Syncytia formation allows the virus to spread without entering the extracellular space, where it might be exposed to immune responses. However, there is evidence that antibodies can also hinder the fusion process. This project uses mathematical analysis to find different possible infection outcomes. A stability analysis of the coinfection model is used to find the fixed points of the model and their stability. This gives us parameter space regions that lead to different possible infection outcomes. Simulations were made to verify the mathematical analysis and see how different syncytia formation properties affect the resulting dynamics. These findings could help develop strategies for controlling viral spread.

PHYS2025HENNESSY3160 PHYS

Analyzing a Mathematical Model for Virus Propagation of the Trachea

Type: Graduate
Author(s): Geoffrey Hennessy Physics & Astronomy
Advisor(s): Hana Drobrovolny Physics & Astronomy

In virology, mathematical models are often deployed to examine and test various behaviors of viruses. For example, one for the flu it is speculated that lethality is linked to the virus’s ability to propagate down the trachea, specifically in how ciliated cells push virus up through mucous layers in a process known as advection. We propose a model for this process, believing that this model can reveal links and critical points between lethality and advection. To solve this model, we utilize three techniques: Laplacian transform, non-linear analysis, and quasi-state analysis. We discuss the findings of each method.

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PHYS2025JOHNSON16587 PHYS

Antiviral Treatment in Syncytia Forming Viruses

Type: Undergraduate
Author(s): Kiara Johnson Physics & Astronomy
Advisor(s): Hana Dobrovolny Physics & Astronomy

Some viruses have the ability to form syncytia. Syncytia are multi-nucleated cells formed via membrane fusion. Syncytia formation allows viruses to spread infection to other cells without entering the extracellular space where it could be exposed to antiviral drugs or immune responses such as antibodies. This project explores how syncytia formation can help viruses avoid antiviral drugs. Drug efficacy parameters are applied to a mathematical model of differential equations to explore the impact of antiviral drugs on cell infection, cell fusion, and viral production to model respiratory syncytial virus. The models show that as syncytia formation increases the drugs become less effective. This information will help physicians treat patients with syncytia forming viruses.

PHYS2025MAKAM7964 PHYS

Cytokine enhancement of oncolytic Sindbis virus

Type: Undergraduate
Author(s): Shriya Makam Physics & Astronomy
Advisor(s): Hana Dobrovolny Physics & Astronomy

Gliomas account for approximately 27% of all primary central nervous system tumors and exhibit highly aggressive growth patterns, making conventional treatments ineffective. Previous research has demonstrated that a replication-competent Sindbis virus (SINV) combined with cytokines (IL-7, IL-12, and GM-CSF) shows promising results in slowing down glioma progression. While prior research demonstrated that SINV combined with cytokines reduces tumor growth, a quantitative understanding of its effects remains limited. This study aims to develop and fit a mathematical model of oncolytic virus infection to data from previous research to quantify key biological processes in glioma treatment. By parameterizing the Sindbis virus-glioma interaction and estimating the effects of cytokine therapy, this model aims to evaluate the efficacy of different SINV variants, with and without cytokine combinations, in controlling tumor growth. We use an Ordinary Differential Equation (ODE) model to describe tumor growth inhibition by the oncolytic SINVs. The model includes variables for uninfected and infected tumor cells, viral load, and cytokine concentration. The data extracted from published tumor growth curves will be used to estimate key parameters, including viral replication rate, tumor growth rate, and cytokine effects. Parameter fitting will be conducted by minimizing the Sum of Squared Residuals (SSR) between model predictions and experimental data. Error in the parameters will be estimated through bootstrapping to find the best fit parameters with 95% confidence intervals. Preliminary analysis suggests that the model effectively captures tumor growth rates observed in the experimental data. Parameter estimation provides insights into the viral infection rate, cytokine-induced tumor suppression, and the timing of viral injections. These findings will help refine our understanding of how the SINVs and cytokine therapy interact in glioma treatment. This study provides a quantitative framework for evaluating the therapeutic effects of an oncolytic SINV combined with cytokines in glioma treatment. By providing parameter estimates for key biological processes, our model can help optimize treatment strategies and guide future experimental research in oncolytic virotherapy.

PHYS2025MCCARTHY52951 PHYS

Structural and Practical Identifiability Analysis of Models for Syncytia Growth

Type: Undergraduate
Author(s): Gabriel McCarthy Physics & Astronomy
Advisor(s): Hana Dobrovolny Physics & Astronomy

Syncytia are multinucleated cells that can occur due to virus infection of cells. Mathematical models in the form of ordinary differential equations can be used to simulate the growth of syncytia. Several novel ODE models can explain syncytia growth. Before employing these models on actual data, it is essential to analyze their structural (theoretical) and practical identifiability using computer software. Structural identifiability is an inherent property of each model and its parameters, referring to our ability to determine parameter values for the model given particular experimental measurements. Practical Identifiability analysis of a model is concerned with determining our ability to accurately determine parameter values given experimental error. Combining these two techniques enables us to determine whether or not the parameters of our syncytia models can be accurately determined. Obtaining accurate parameter values allows us to make conclusions about our data that can provide insight into the nature of the spread of syncytia. From this, we can plan experiments to parameterize the syncytia growth in the contexts of our models.

PHYS2025MCCARTHY8679 PHYS

Applications of Mathematical Models of Virus to Mpox

Type: Undergraduate
Author(s): Gabriel McCarthy Physics & Astronomy
Advisor(s): Hana Dobrovolny Physics & Astronomy

Mpox virus is a type of virus similar to smallpox that can cause diseases in humans. Several experiments have been done to collect data on how mpox evolves within an infected host. This data can be analyzed within the context of mathematical models to determine important characteristics of mpox. From this analysis, we can estimate the growth rate, reproduction number, and infecting time of mpox.  We can also construct confidence intervals to estimate the error in our predictions using bootstrapping.  Bootstrapping allows us to analyze parameter correlations within mpox data to understand how parameter values within the model affect each other in our model. From these values and confidence intervals, we can learn about how mpox evolves within the body over time. This information, in turn, may allow us to make predictions on how mpox evolves within people during infection that could inform future treatment regimens.

PHYS2025PADMASOLALA6496 PHYS

Comparison of oncolytic herpes simplex virus strains in treatment of EGFR-bearing tumors

Type: Undergraduate
Author(s): Raghav Padmasolala Physics & Astronomy
Advisor(s): Hana Dobrovolny Physics & Astronomy

Oncolytic Herpes Simplex Viruses (oHSVs) target a wide range of different cells and specific mutations, allowing them to proliferate in tumor cells. Recent work has modified the virus to preferentially enter cells bearing epidermal growth factor receptors (EGFRs). This study focuses on characterizing the efficacy of different strains of EGFR-targeting oHSV by fitting a mathematical model that includes an interferon response to experimental data from U251 tumor-bearing mice. Using a combination of parameter fitting, optimization techniques, and ordinary differential equations (ODEs), we modeled tumor growth, viral dynamics, and immune response. Our findings suggest that an interferon-inclusive model best explains the growth and oHSV treatment of EGFR-bearing tumors. These results highlight the importance of immune interactions in oncolytic viral therapy and contribute to optimizing oHSV-based treatments for better clinical outcomes.

PHYS2025PHAM49939 PHYS

Room Temperature Phosphorescence with Direct Triplet State Excitation

Type: Undergraduate
Author(s): Danh Pham Physics & Astronomy
Advisor(s): Zygmunt Gryczynski Physics & Astronomy

PHYS2024AHLUWALIA65139 PHYS

GaOOH: A Novel Antimicrobial Agent

Type: Undergraduate
Author(s): Pavan Ahluwalia Physics & Astronomy Dustin Johnson Physics & Astronomy Yuri Strzhemechny Physics & Astronomy
Advisor(s): Yuri Strzhemechny Physics & Astronomy
Location: Basement, Table 15, Position 1, 1:45-3:45

Gallium oxide is a wide-bandgap semiconductor gaining significance for its outstanding optoelectronic and gas-sensing properties. Although gallium oxide is known for its antibacterial efficacy, limited research is available on the antimicrobial properties of gallium oxyhydroxide (GaOOH). This study investigates GaOOH's antibacterial action by examining the effect of the growth solution's pH on its chemical and physical properties and their correlation with bacterial growth inhibition. The hydrothermal method was used to synthesize GaOOH microparticles (MPs). Deionized water, ammonium hydroxide, and gallium nitrate hydrate salt were mixed to create samples with pH levels ranging from 5 to 10 at 60°C. Subsequent analysis, including scanning electron microscopy, Fourier-transform infrared (FTIR) spectroscopy, and photoluminescence spectroscopy, revealed that higher pH levels increased the average GaOOH MPs length and created more crystal lattice defect sites. The correlation between surface chemistry and pH was evident in the position of higher energy FTIR Ga-OH bending bands. Antibacterial studies demonstrated a greater inhibition of Escherichia coli, a Gram-negative bacterium, at higher pHs. This suggests a potential role of defect sites in GaOOH's antimicrobial activity. There was significant inhibition of Staphylococcus aureus growth. However, no conclusive correlation with pH was established, possibly due to the characteristics of the Gram-positive cell wall. Future studies should further explicate the relationship between GaOOH MPs morphologies and growth inhibition of Escherichia coli and Staphylococcus aureus.

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PHYS2024BRANNON63900 PHYS

Egyptian Blue Nanosheets as a Novel Bioimaging Agent

Type: Graduate
Author(s): John Brannon Physics & Astronomy
Advisor(s): Yuri Strzhemechny Physics & Astronomy Anton Naumov Physics & Astronomy
Location: First Floor, Table 1, Position 2, 1:45-3:45

Since the ancient times, a common pigment used for expression in clothes and art was egyptian blue (EB). Today, instead of using this cuprous silicate as a way for one’s personal expression, we will provide reasons why this pigment can be used as a novel bioimaging agent for cell work. Finding another bioimaging agent for cell-use is always an advantage because each agent supplies their own advantages when working in cells. So the more agents we have in our possession, the more angles we can take on a problem. To be considered a bioimaging agent, it needs to dissolve in polar solvents (mainly water), be non-toxic, and display fluorescence in the near-infrared range of the optical spectrum. EB has all three of these properties with the right preparation. Sonicating EB reduces their size to become extremely small sheets, which increases interaction with water molecules to ultimately allow the sheets to dissolve within the water solvent. These sheets are on the nanoscale, so they will be referred to as EB nanosheets (EBNS). EBNS fluoresce in the near infrared and have no history of being toxic. EBNS have the capability of emitting more photons per photons absorbed compared to most materials (high quantum number). This novel material also does not quench fluorescently as easily as other agents due to its copper atoms. EBNS have strong Raman vibrational modes that can help image cells too. We want to highlight why EBNS can be an effective platform for future bioimaging applications and ultimately, cancer imaging/treatment applications.

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PHYS2024CHIARELLI52733 PHYS

Temperature dependence of syncytia formation

Type: Undergraduate
Author(s): Aubrey Chiarelli Physics & Astronomy
Advisor(s): Hana Dobrovolny Physics & Astronomy
Location: Second Floor, Table 2, Position 3, 11:30-1:30

Several viruses have the ability to cause cells to fuse together into large multinucleated cells called syncytia. It is known that syncytia help the virus propagate without leaving the cell, however it is unknown how the formation rate is affected by temperature. This project aims to use mathematical modeling to investigate the rate of syncytia formation in the HIV virus as temperature varies. A cell-cell fusion mathematical model was used to analyze data from cell-cell fusion assays at various temperatures. Parameters were estimated via minimization of squared residuals, with uncertainties assessed through bootstrapping. These findings could help develop strategies for controlling viral spread.

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PHYS2024DORSKY52600 PHYS

Shining Brighter: Folic Acid GQD Synthesis

Type: Undergraduate
Author(s): Abby Dorsky Physics & Astronomy Olivia Sottile Biology
Advisor(s): Anton Naumov Physics & Astronomy

Cell imaging is an important tool in cancer diagnosis and therapy. Folic acid receptors are overexpressed on the surface of various cancer cells, making it an attractive target for cancer imaging. In our research, we aim to exploit this biological phenomenon by creating Folic Acid Graphene Quantum Dots (GQDs) that can help us selectively target and visualize cancerous tissue. GQDs were used as a base due to their easy functionalization abilities, high cellular viability, and fluorescent properties that allow them to be tracked inside the cell. We functionalized GQDs with folic acid and assessed their structure and morphology as well as optical properties using FTIR, TEM, absorption, and fluorescence spectroscopies. The efficacy of the FA-GQDs is evaluated through their internalization study in cancerous (HeLa) cells at hours 1,6,12, 24, and 48 by utilizing the intrinsic fluorescence of FA-GQDs. In vitro toxicity tests have shown low toxicity (80% viability) of the synthesized FA-GQDs. The proposed FA-N-GQDs provide a novel platform for the detection of cancerous tissues and could be used as a cancer diagnosis biodevice.

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PHYS2024GEBHART48661 PHYS

Explosive galactic weather: Winds from the largest cloud in the local group

Type: Undergraduate
Author(s): Stone Gebhart Physics & Astronomy Katherine Anthony Physics & Astronomy Lauren Sdun Physics & Astronomy
Advisor(s): Kat Barger Physics & Astronomy
Location: Third Floor, Table 8, Position 1, 11:30-1:30

The Large Magellanic Cloud (LMC), a small neighboring galaxy around one Milky Way diameter away, provides a unique opportunity to study outflowing gas clouds in great detail. Massive stars in the LMC undergo supernova explosions when they die, blasting gas in all directions. If the gas escapes from the galaxy, a galactic wind is formed. Using data from the Hubble Space Telescope, we can try to better understand how this wind moves and its physical properties. Because there can be numerous of these gas clouds in each direction, we often detect complex patterns that we are characterizing with a Gaussian fitting algorithm. Thoroughly studying the resolved galactic wind of the LMC will ultimately contribute to our understanding of the processes that drive galaxy evolution.

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PHYS2024GERG27594 PHYS

Quantifying Spatial Heterogeneity of Syncytial Cells using Alpha Shapes

Type: Graduate
Author(s): Anthony Gerg Physics & Astronomy
Advisor(s): Hana Dobrovolny Physics & Astronomy
Location: Third Floor, Table 3, Position 2, 1:45-3:45

We introduce a structural method used for quantifying the spatial heterogeneity(or clumpiness) of viral syncytial cells in a transfected bioassay. The solution lies in an inter-disciplinary process based on simplicial topology being applied to a biological system. Our method revolves around using topological theories including Delaunay Tessellations and Voronoi Graphs to signify cell-cell interaction probability. The main emphasis is the subset of Delaunay Tessellation called Alpha Shapes. By applying a filtration to the overall Delaunay Tessellation, we can obtain unique Alpha Shapes that have cell-cell interactions removed. The emphasis of the filtration is to find the correct shape where there were no connection crossing syncytia, only between healthy neighborhoods of cells. The process allows for the associated alpha number to be assigned to the clumpiness. Alpha numbers can then be used to separate different bioassays, or quantify temporal changes found in a single viral transfection due to syncytia.

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PHYS2024HORTON31355 PHYS

Go with the Flow: Measuring the Physical Properties of the Magellanic Stream

Type: Graduate
Author(s): April Horton Physics & Astronomy Kat Barger Physics & Astronomy Frances Cashman Physics & Astronomy Andrew Fox Physics & Astronomy Dhanesh Krishnarao Physics & Astronomy Scott Lucchini Physics & Astronomy Naomi McClure-Griffiths Physics & Astronomy Suraj Poudel Physics & Astronomy Jo Vazquez Physics & Astronomy
Advisor(s): Kat Barger Physics & Astronomy
Location: Second Floor, Table 3, Position 3, 11:30-1:30

Massive stars die through powerful supernova explosions, which produce clouds of gaseous debris that can be propelled to the outskirts of the galaxy. The material on the outer edge is more vulnerable to processes occurring in the environment. These processes pull and tug the debris and can form a gaseous stream flowing from the galaxy. One prominent example in the night sky is the Magellanic Stream (MS), which flows out of our neighboring galaxy, the Large Magellanic Cloud (LMC). With observations from the Hubble Space Telescope, we are examining the absorption features of light from background stars that pass through the gaseous material of the MS enabling us to measure its physical properties. We traced the small-scale motion of the neutral hydrogen gas using emission-line data from the Galactic All-Sky Survey and the Galactic Australian Square Kilometre Array Pathfinder programs to determine where the MS begins relative to the LMC. Comparing these observations, we find the MS in the absorption spectra on the nearside of the LMC between +235 ≤ vlsr ≤ +350 km/s. By investigating the physical properties of the MS, we can better understand how the environmental processes shaped its formation.

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PHYS2024JOHNSON8395 PHYS

Studies of Surface Defect in Microcrystalline α-GaOOH and β-Ga2O3

Type: Graduate
Author(s): Dustin Johnson Physics & Astronomy Pavan Ahluwalia Physics & Astronomy Tiffany McHenry Physics & Astronomy Zachary Rabine Physics & Astronomy Madeline Smit Physics & Astronomy
Advisor(s): Yuri Strzhemechny Physics & Astronomy
Location: Basement, Table 4, Position 2, 1:45-3:45

Surface defects in nano- and micro-crystals strongly affect performance of materials in applications, necessitating elucidation and control of those defects. The beta variant of gallium oxide (β-Ga2O3) in nano- and microcrystalline form is attracting a strong interest due to its potential applications in such critical areas as biological therapeutics, optoelectronics, and catalysis. In our studies, β-Ga2O3 crystals are produced through a simple bottom-up hydrothermal method, which yields, as a first step, an α-GaOOH precursor, which then undergoes calcination to bear the final product. Variation of growth parameters allows for a synthesis of particles with tunable morphologies and surface structures. Optoelectronic and physicochemical properties of both α-GaOOH & β-Ga2O samples are studied by a range of experimental techniques. These investigations address, among others, the surface defect properties. We also evaluate the impact of surface defects and particle morphologies on the antibacterial action α-GaOOH.

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PHYS2024KALLUHOLEMATHAM15498 PHYS

Cathodoluminescence as a means of studying GaOOH and Ga2O3

Type: Undergraduate
Author(s): Devansh Matham Physics & Astronomy Dustin Johnson Physics & Astronomy Tiffany McHenry Physics & Astronomy Madeline Smit Physics & Astronomy Yuri Strzhemechny Physics & Astronomy
Advisor(s): Yuri Strzhemechny Physics & Astronomy
Location: Basement, Table 1, Position 3, 1:45-3:45

Currently our lab is designing a system that allows us to leverage cathodoluminescence spectroscopy to study the optoelectronic properties of gallium oxyhydroxide and gallium oxide. This system would allow us to place our samples within a vacuum chamber and irradiate it with a high-energy electron beam, causing light emissions that are then collected by a fiber optic cable. This optical system allows us to capture the emissions and investigate them as its characteristics are dependent on the material properties of the sample. Furthermore, since we are working in ultra-high vacuum conditions, the components of the system have to be designed with careful consideration, in addition to allowing several degrees of freedom in order to precisely position our sample within the vacuum chamber.

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PHYS2024KAVOOR45385 PHYS

Using mathematical modeling to characterize the effectiveness of different oncolytic herpes viruses

Type: Undergraduate
Author(s): Aditi Kavoor Physics & Astronomy
Advisor(s): Hana Dobrovolny Physics & Astronomy
Location: Basement, Table 11, Position 1, 1:45-3:45

The herpes virus, like many other viruses, can be engineered to target and kill cancer cells. The herpes virus, when loaded with immune stimulating factors, like interleukin 12, can be even more effective at killing cancer cells. We use a mathematical model of oncolytic virus infection and apply it to experimental data from Fukuhara et al. (2023) to assess the effectiveness of different herpes virus strains in treating cancer. We are able to estimate virus characteristics such as viral production rate and infectious lifespan of the different strains, allowing for a quantitative comparison. This type of analysis can help identify which strains are most effective at killing tumors.

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PHYS2024MALKOTI11205 PHYS

Modeling pulsed drug treatment with a constant drug in cancer growth models

Type: Undergraduate
Author(s): Prateek Malkoti Physics & Astronomy
Advisor(s): Hana Dobrovolny Physics & Astronomy
Location: First Floor, Table 5, Position 1, 1:45-3:45

Researchers use mathematical models of cancer to study the effectiveness of different regimens of chemotherapy when treating tumors. These models help predict how different treatments affect cancer cell growth in hopes of determining which will effectively kill a tumor. Realistic pulsed drug treatments are computationally expensive and difficult to analyze mathematically. We examine when the effect of a pulsed drug treatment can be well-represented by a constant dose model. Our approach studies treatment applied in various cancer growth patterns, such as exponential, linear, logistic, Mendelsohn, surface, Gompertz, and Bertalanffy models. Mathematically modeling and analyzing the comparison between tumor growth under a pulsed drug treatment and under a constant dose helps us understand when the use of the simpler model can make accurate predictions.

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PHYS2024MCCARTHY60528 PHYS

Structural and Practical Identifiability Analysis of Models for Syncytia Growth

Type: Undergraduate
Author(s): Gabriel McCarthy Physics & Astronomy
Advisor(s): Hana Dobrovolny Physics & Astronomy
Location: Basement, Table 5, Position 3, 11:30-1:30

Syncytia are the multinucleated cells that can occur due to virus infection of cells. Mathematical models in the form of ordinary differential equations can be used to simulate the growth of these infections. Several ODE models can explain syncytia growth. Before employing these models on actual data, it is essential to analyze their structural and practical identifiability. Structural identifiability is an inherent property of each model and its parameters, referring to our ability to determine parameter values for the model. Practical Identifiability analysis of a model is concerned with accurately determining parameter values given experimental error. Obtaining accurate parameter values allows us to make conclusions about our data within the context of our model that can provide insight into the nature of the spread of syncytia. These two techniques allow us to determine whether or not the parameters of a model are identifiable with the data we plan to collect. Consequentially, we can plan experiments adequately to truly parameterize the data in the contexts of our model and make accurate conclusions.

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PHYS2024MCHENRY4640 PHYS

Hydrothermal Synthesis and Characterization of Gallium Oxide Micro and Nanocrystals

Type: Undergraduate
Author(s): Tiffany McHenry Physics & Astronomy Pavan Ahluwalia Physics & Astronomy Dustin Johnson Physics & Astronomy Devansh Kalluhole Physics & Astronomy Madeline Smite Physics & Astronomy Yuri Strzhemechny Physics & Astronomy
Advisor(s): Yuri Strzhemechny Physics & Astronomy
Location: Second Floor, Table 6, Position 2, 1:45-3:45

Currently, research of gallium oxide (GO) nano- and microcrystals is rapidly expanding with the demand for potential uses. GO has been shown to be a promising material for possible applications in many different fields including photocatalysis, biomedicine, and optoelectronic devices. In our lab (led by Dr. Strzhemechny) we examine both the fundamental (nature of crystal defects) and applied (antibacterial action) properties of GO. During the hydrothermal growth process of GO, we are producing different nano and microscopic morphologies of this material by controlling various growth parameters including varied pH and adding surfactants to the material. The synthesis procedure includes using the precursor material, gallium nitrate hydrate, ammonium hydroxide. We use a calcination furnace that can get to temperatures high enough to effectively synthesize GO. Now, with a thermocouple and pyrometer we can predict outcomes during the calcination step with high accuracy and precision.

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PHYS2024MYERS54098 PHYS

Tracing the Chemistry of the Milky Way: Radial Variation and the Identification of Supernova Fingerprints

Type: Graduate
Author(s): Natalie Myers Physics & Astronomy John Donor Physics & Astronomy Jonah Otto Physics & Astronomy Taylor Spoo Physics & Astronomy Alessa Wiggins Physics & Astronomy
Advisor(s): Peter Frinchaboy Physics & Astronomy
Location: Third Floor, Table 10, Position 1, 11:30-1:30

Open clusters are groups of stars with the same age, chemistry, and velocity. These characteristics make open clusters powerful tools for tracing the dynamic and chemical evolution of our home galaxy, the Milky Way. The goal of the Open Cluster Chemical Abundance and Mapping (OCCAM) survey is to identify and analyze a large sample of open clusters with a wide range of chemical abundances. To do this, it utilizes the infrared spectra provided by the Sloan Digital Sky Survey’s (SDSS) APOGEE spectrograph and the kinematic data from the Gaia Space Telescope to form a large survey of open clusters with uniformly derived chemical abundances (e.g., C, Mg, Si, Al, Fe, Ni). Here, we present the results from the OCCAM analysis of the latest SDSS/APOGEE data release. This dataset of 153 different open clusters, including 2061 individual stars, is used to investigate the variation of the Milky Way’s chemistry for multiple different abundance groups. In addition to this dataset, we also present the current status of new optical observations that will allow us to expand the wavelength coverage for each star and trace more elements. These new observations enable us to accurately decipher the chemical fingerprints from ancient supernovae (e.g., Y, Ba, Ce, Nd, Eu) and expand our analysis.

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PHYS2024OTTO6504 PHYS

Digging through the Galactic Graveyard: Chemistry and Ages of “Dead” Milky Way Satellite Galaxies

Type: Graduate
Author(s): Jonah Otto Physics & Astronomy Taylor Spoo Physics & Astronomy Ellie Toguchi-Tani Physics & Astronomy
Advisor(s): Peter Frinchaboy Physics & Astronomy
Location: Second Floor, Table 5, Position 3, 11:30-1:30

Characterizing Galactic sub-structures is crucial to understanding the assembly history and evolution of the Milky Way. To accomplish this, we need to identify and analyze the accreted sub-structures. With ESA Gaia and SDSS-IV/APOGEE, studies have been done to analyze the kinematics and chemical abundances, respectively. However, one challenge that still remains is deriving reliable ages for these sub-structures. We utilize the new relationship between the carbon to nitrogen ratio and stellar age derived by the OCCAM team, which has recently been extended to the metal-poor regime, to probe stars within the sub-structures in the metallicity range -1.2 ≤ [Fe/H] ≤ +0.3 dex. This allows us to determine the ages of a greater number of stars within these sub-structures, which paints a more coherent picture of the original galaxies that have been disrupted to form the Milky Way’s halo. Using the sample of halo sub-structures in Horta et al. (2023), we apply the newly extended calibration to determine ages of stars within these sub-structures and compare them to previous age estimates.

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PHYS2024PANDA61113 PHYS

Tiny Dots, Big Feelings: Graphene Quantum Dots Sniffing Out Dopamine

Type: Graduate
Author(s): Mudit Panda Physics & Astronomy Tejas Sukesh Physics & Astronomy Ugur Topkiran Physics & Astronomy Alina Valimukhametova Physics & Astronomy
Advisor(s): Anton Naumov Physics & Astronomy
Location: Third Floor, Table 4, Position 2, 11:30-1:30

Graphene quantum dots (GQDs) is an emerging nanocarbon platform that is now actively utilized for therapeutic applications. Their increasing popularity arises due to relatively high biocompatibility, water solubility, optical properties enabling multi-color fluorescence imaging and the ease of functionalization with a variety of therapeutic agents. Such properties pave the way for a variety of imaging and sensing applications. Herein, we are utilizing rGQDs (reduced graphene quantum dots) synthesized top down from reduced graphene oxide for dopamine sensing. Detecting dopamine can provide insights about the neural health and the activity of neurotransmitters in the brain. However, due to the presence of dopamine receptors throughout our body, this will also help assess other vital functions including secretion of pituitary hormones [1], gut motility [2], immunomodulatory effects in inflammation-related diseases [3][4] and cardiovascular effects (dopamine can act as both autocrine or paracrine compound in the mammalian heart) [5]. In our work rGQD near-infrared (NIR) fluorescence appears to react proportionally to dopamine concentration within the range of 1000ng/ml – 1ng/ml as assessed with NIR fluorescence imaging of dopamine/rGQD interactions on cotton discs and biocompatible gels as well as with NIR fluorescence spectroscopy. This rapid NIR response and the capability of dopamine sensing in gel matrix suggests the potential for detection of blood-relevant dopamine concentrations in vivo, which will be explored with GQD-based implantable sensors. In addition to the development of a novel non-invasive dopamine sensing mechanism, the present study will aid in gaining valuable insight into GQD properties in vivo and their potential for in vivo analyte detection.
References:
1. Nira Ben-Jonathan, Robert Hnasko, Dopamine as a Prolactin (PRL) Inhibitor, Endocrine Reviews, Volume 22, Issue 6, 1 December 2001, Pages 724–763, https://doi.org/10.1210/edrv.22.6.0451
2. Graeme Eisenhofer, Anders Åneman, Peter Friberg, Douglas Hooper, Lars Fåndriks, Hans Lonroth, Béla Hunyady, Eva Mezey, Substantial Production of Dopamine in the Human Gastrointestinal Tract, The Journal of Clinical Endocrinology & Metabolism, Volume 82, Issue 11, 1 November 1997, Pages 3864–3871, https://doi.org/10.1210/jcem.82.11.4339
3. Channer B, Matt SM, Nickoloff-Bybel EA, Pappa V, Agarwal Y, Wickman J, Gaskill PJ. Dopamine, Immunity, and Disease. Pharmacol Rev. 2023 Jan;75(1):62-158. doi: 10.1124/pharmrev.122.000618. Epub 2022 Dec 8. PMID: 36757901; PMCID: PMC9832385.
4. Feng YF and Lu Y (2021) Immunomodulatory Effects of Dopamine in Inflammatory Diseases. Front. Immunol. 12:663102. doi: 10.3389/fimmu.2021.663102
5. Neumann J, Hofmann B, Dhein S, Gergs U. Role of Dopamine in the Heart in Health and Disease. Int J Mol Sci. 2023 Mar 6;24(5):5042. doi: 10.3390/ijms24055042. PMID: 36902474; PMCID: PMC10003060.

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PHYS2024SRIVASTAVA9783 PHYS

A mathematical model of triple viral infection

Type: Undergraduate
Author(s): Saanvi Srivastava Physics & Astronomy
Advisor(s): Hana Dobrovolny Physics & Astronomy
Location: Third Floor, Table 3, Position 3, 1:45-3:45

This study addresses the escalating concern over the interaction of multiple respiratory viruses by introducing a mathematical model to analyze triple infection dynamics involving influenza (IAV), respiratory syncytial virus (RSV), and SARS-CoV-2. With the ongoing COVID-19 pandemic and the resurgence of RSV, understanding the dynamics of triple infections is critical for public health preparedness. Comprehending the interactions among these viruses is crucial for improving our capacity to forecast and curb disease outbreaks. The central question addressed in this study is how variations in infection rates influence the duration and maximum population size of each virus in a triple infection scenario. Prior research has explored coinfections involving two respiratory viruses, yet triple infections, especially among adults, remain infrequent and poorly elucidated. The urgency to address these questions arises from the potential for overwhelming hospitals and exacerbating disease burden, especially in vulnerable populations. By developing a mathematical model to analyze triple infections, this research aims to provide insights that can inform public health strategies and mitigate the impact of respiratory virus outbreaks. Through extensive simulations, the study evaluates how variations in infection rates influence the duration and maximum population size of each virus. The findings unveil intriguing patterns: while SARS-CoV-2 demonstrates remarkable resilience across various infection rates, influenza and RSV display more nuanced responses, exhibiting sensitivity to changes in transmission rates.

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