After-school programs can provide a variety of opportunities for elementary school students. With support from the Experiential Projects to Impact the Community (EPIC) committee, we partnered with a local elementary school in the Crowley Independent School District (CISD) to start a pickleball program. Pickleball is one of the fastest-growing sports in America. The sport combines elements from tennis, badminton, and table tennis. The sport is appealing to all ages because it is easy to play. We gauged students' interest by teaching pickleball twice a week during P.E. classes. The Meadowcreek Pickleball Club launched shortly after in January of 2022. Students meet weekly to participate in drills, games, and clinics. Funding from the EPIC grant and a partnership with the Selkirk Growth Program allowed us to supply the school with nets, balls, and paddles. The purpose of the Meadowcreek Elementary Pickleball Club is to provide a safe environment where fourth and fifth graders can build relationships, gain confidence, and learn new skills.

According to the National Center for Education Statistics, White, Latino/a, and Black youth enter into STEM programs at their universities in virtually identical numbers. Unfortunately following the early years of admittance, this is where the previous trend takes a dramatic decline as Black and Hispanic students are more likely to switch out of this field at rates of 40% and 37%, respectively (Riegle-Crumb et al., 2019). These disparities within Black and Hispanic communities regarding retention rate in STEM can oftentimes be attributed to factors such as imposter syndrome, lack of educational resources, and a lack of guidance/mentorship during their undergraduate career– the latter being the main focal point of this study. The purpose of this research is to analyze the impact that mentoring programs have on minority high school students that are interested in pursuing a degree in the field of STEM. Pre- and Post-surveys were utilized during the 2020/2021 academic school year in order to accurately gauge the students’ confidence in the following: applying to STEM programs at their universities of interest, excelling once admitted, and the amount of support they have in doing so. Community Partners include two local high schools in the surrounding DFW metroplex where students are paired with TCU Undergraduates currently pursuing a degree in STEM. Ultimately the following research seeks to examine the effectiveness of mentoring programs in the removal of generational barriers that have historically prevented populations of first-generation, minority students from not only succeeding in institutions of higher education, but ultimately receiving a bachelor's degree within fields of science, technology, engineering, and mathematics.

Separated from their families, many older Americans in assisted living facilities struggle with loneliness and social isolation. The COVID-19 pandemic has only exacerbated this issue, for most facilities have restricted outside visitors due to safety concerns. With the help of the Experiential Projects to Impact the Community (EPIC) Grant, which provides up to $1,500 for a Pre-Health student-led project at TCU that promotes a culture of giving and serves a demonstrated need in the Fort Worth community, a monthly meeting, centered on a craft activity, entitled “Crafts and Conversations” was established at Trinity Terrace to foster community between students at TCU and the residents of a local retirement facility. Through monthly Zoom meetings during the height of the pandemic to masked in-person gatherings at Trinity Terrace, TCU undergraduate students and residents at Trinity Terrace could talk amongst each other while constructing a craft whether that be painting Halloween pumpkins or crafting a winter holiday snow globe. By volunteering in leading these crafts, TCU students have had the chance to build meaningful relationships, improve upon their communication skills in a group dynamic, and been able to address preconceived stereotypes about the elderly. Prior to each craft, each meeting opens with a musical performance that has allowed TCU undergraduate musicians to cultivate and share their craft as well. This project has helped give residents at Trinity Terrace an outlet for social connections through crafts and conversations. Through a commitment to sustainability, “Crafts and Conversations” with Trinity Terrace will endure as a lasting legacy through a crew of committed volunteers who have grown as student leaders by strengthening the Fort Worth community and enriching the lives of the residents at Trinity Terrace.

The Pre-Health Peer Mentor EPIC grant program initiated our Once Upon a Room project to provide individual room decorations to patients at Cook Children. Due to ongoing COVID-19 pandemic, we pivoted our goals by creating gift bags for patients and their families. These bags included gifts to make their stay better, from holiday bags including board games, toys, and other sensory items to welcome bags with hygiene supplies for parents. We have delivered approximately 45 bags in the Fall 2021 and Spring 2022 semesters and are set to deliver approximately 36 more in coming months. The gift bags have been a success with consistent and positive feedback from family and from Cook Children's Child Life department alike.

In this project we examine 2-dimensional cell-complexes and group actions on those cell complexes. We determine topological invariants of the group actions on these complexes using homology, cohomology, and the Euler characteristic.

In the field of Riemannian geometry, the condition on the Riemannian metric so that a manifold has positive scalar curvature (PSC) is important for a number of reasons. Many famous researchers have contributed gradually to this area of geometry, and in this project, we study more about PSC metrics on such manifolds. Specifically, we refine and provide some details to the proof of Gromov and Lawson that the connected sum of 2 n-dimensional manifolds will admit a PSC metric, provided each of the manifolds has a metric with the same condition. We then derive some useful formulas related to the Riemann curvature tensor, the Ricci tensor, and the scalar curvature in many different scenarios. We compute the quantities for a manifold equipped with an orthonormal frame and its dual coframe, namely the connection one-form and the curvature two-form. Then, we observe the change in the structure functions, defined as a function that determines the Lie derivative of the orthonormal frame, under a nearly conformal change of the said frame. The aim of these calculations is that, by expressing the scalar curvature of a manifold M entirely in terms of the structure functions, we can determine a condition on the conformal factor so that when dividing the tangent bundle of M into two sub-bundles, then the scalar curvature restricted to one sub-bundle will “dominate” that of the other one so that if we know the scalar curvature of the former sub-bundle is positive, we can be assured that the scalar curvature of M as a whole is also positive.

This research project focuses on the spreading of random curves in the differential geometry field which arises in statistical mechanics . It is known from the work of Einstein that random walks are connected to Brownian motion and diffusion. We will examine random curves that are not merely continuous but that are smooth and have prescribed bounds on curvature. We examine the distribution of a finite number of endpoints of such random curves. Using Python, we obtain 2-D histograms, graphs, and charts to research the spreading of random curves. A central goal in statistical mechanics is to describe the large-scale behavior of systems with the distribution of randomly generated data; we compare the distributions of curve endpoints to the Gaussian (normal) distribution.

Omega-3 supplementation in Division I track & field and cross-country athletes: Physiological markers of Omega-3 status, compliance, and likeability

Katie Couris1, Daphne Thomas1, Tatum Johnston1, Austin J Graybeal, PhD, CSCS2, Brooke Helms, MA, RDN, CSSD, LD3, and Jada L. Willis, PhD, RDN, LD, FAND1

1Department of Nutritional Sciences, College of Science & Engineering, Texas Christian University; Fort Worth, TX
2School of Kinesiology and Nutrition, University of Southern Mississippi; Hattiesburg, MS
3TCU Sports Nutrition, Department of Athletics, Texas Christian University, Fort Worth, TX

ABSTRACT
Omega-3 fatty acid (FA) intake is suboptimal in student-athletes. Given this, and the newfound access to supplementation in collegiate athletes, the purpose of this study was to determine if Enhanced Recovery™ (ER) would improve FA profiles, compliance, and likeability versus a control in Division I track & field and cross-country athletes. In this randomized crossover study, 17 athletes were randomly assigned to either ER or a matched, standard control (fish-oil pills) for ~42d each with a 33-35d washout period. FA profiles were measured at baseline and every two-weeks. For omega-3 index (N3I), there were significant effects of time (p<0.001) and interaction (p=0.004). Significant increases were observed up to four-weeks and were higher for the control versus ER at weeks four (ER=7.25%±1.02; CON=7.76%±1.16) and six (ER=7.33%±1.14; CON=8.03%±1.33). There were also significant effects of time for omega-3:6 and arachidonic:eicosapentaenoic acid (p<0.001). However, after adjusting for compliance and consumption of omega-3 food sources, there were no longer significant effects of time, but an interaction effect remained for N3I and was observed for omega-3:6 (p=0.022; p=0.024, respectively) where both measures were better from four-to-six weeks during the control. Consumption of omega-3 food sources was a significant covariate for N3I and omega-3:6 (p=0.037; p=0.017, respectively). Lastly, 57.9% reported liking/being more likely to take ER and felt it was easier to consume (68.4%). As expected, both the ER and control led to improved FA levels. However, supplementation with ER led to improved likability among division I athletes which may enhance long-term omega-3 status.

Dark Matter (DM) is hypothesized to be an exotic particle that is invisible to human observation. But thankfully, its existence is proven through its gravitational interaction with luminous matter (such as stars and galaxies), and it is responsible for the formation of the humongous structures across our universe. The leading interpretation of DM is what we call Cold Dark Matter (CDM), where the DM particles have relatively low velocities and low energies. This causes structures to form quite quickly and easily in the early universe. While CDM can explain many observed properties of the universe, it is not without its flaws (specifically on the scale of low-mass dwarf galaxies). The hypothesis of Warm Dark Matter (WDM) poses a viable solution to the shortcomings of CDM. In WDM, the DM particles are of higher energy and have higher velocities. This would cause the formation of the first gravitationally bound structures in the Universe to be delayed when compared to CDM. Using a model to approximate varying temperatures of DM, we compare the rates and characteristics of early structure formation for the current CDM hypothesis, and that of many other types/temperatures of WDM. We expect that the differences between CDM and WDM will be most apparent during the first billion years after the Big Bang, just as the first stars in the Universe ignite. These results may be indicative of the true nature of dark matter, and finally bring our understanding into the light.

Graphene Quantum Dots (GQDs) are highly perspective bioimaging agents due to a plethora of advantageous properties making them superior to conventional fluorophores. Those properties include stability to photobleaching, large Stokes shifts circumventing biological autofluorescence, and a capability of functionalization for drug delivery. In this work, a variety of GQD structures are imaged via visible fluorescence microscopy in order to evaluate the optimal GQD structures for bioimaging and bioengineering in vitro.

Infections deriving from the highly pathogenic avian H5N1 influenza virus often result in severe respiratory diseases with a high mortality rate. Although rarely transmissible to humans, recent events such as the SARS-CoV-2 pandemic have shown that a proper understanding of the life cycles of deadly viruses like H5N1 and any variables that affect its terminality are vital. One such variable could be the method of entry, and its impact on the progression of H5N1 is the focus of the study. Utilizing previous data on cynomolgus macaques subject to samples of H5N1, we study how entry via a combined intrabronchial, oral, and nasal pathway affect disease progression. We fit the data using a viral kinetics model, which allows us to estimate parameters describing the H5N1 life cycle. This allows us to better understand the life cycle of H5N1 in vivo.

Everyone gets sick and illness negatively affects all aspects of life. One major cause of illness is viral infections. Some viral infections can last for weeks; others, like influenza (the flu), can resolve quickly. During infections, healthy cells can grow in order to replenish the cells that have died from the virus. Past viral models, especially those for short-lived infections like influenza, tend to ignore cellular regeneration – since many think that uncomplicated influenza resolves much faster than cells regenerate. This research accounts for cellular regeneration, using an agent-based framework, and varies the regeneration rate in order to understand how cell regeneration affects viral infections. The model used represents virus infections and spread in a two-dimensional layer of cells in order to generate graphs of virus over time for corresponding regeneration rates. We find that the effect of cell regeneration depends on the mode of transmission of the infection.

Photothermal Therapy (PTT) provides a promising new method of radiative therapy cancer, using infrared wavelengths. In my project, the ability of these materials to heat up when shone with near infrared light, or the photothermal effect, of various nanomaterials—including reduced graphene oxide, reduced graphene quantum dots , and copper sulfide nanoparticles—is characterized by irradiation of the aqueous materials with near-infrared radiation.

With the onset of the SARS-CoV-2 pandemic in the U.S. in early 2020, much of the early response in the U.S. was made on a state level with varying levels of effectiveness. To characterize the effects of early preventative measures by state legislatures we can use a SEIR model and data gathered to analyze the effectiveness of lockdown measures from state to state. Using the data collected we can model the effect of lockdown measures on the infection rate to characterize the effect preventative measures had on case numbers. We chiefly used 4 models to simulate the change in infection rate: instantaneous, linear, exponential, and logarithmic. Then using these models, we fit each model to the case data and compared the relative accuracy of each model to the data to determine which model most accurately represented the change in infection rate within the first months of the pandemic. Following this, we used the fits obtained to create a possible distribution for each parameter, which helps accurately predict the actual number of cases and how it was affected by preventative measures.

Several different vaccines have been introduced to combat the spread of SARS-CoV-2 infections. As the virus is capable of mutating to escape the protection given by the vaccine, using multiple vaccines is believed to help prevent the virus from mutating to escape all vaccines, helping to combat spread of the virus. We simulate the effect of using multiple vaccines on the virus using a mathematical model. With the model, we can better understand the effect of multiple types of vaccines in helping to control pandemics.

Oxidative stress, an imbalance of reactive oxygen species, has been shown to participate in a multitude of diseases from Alzheimer to cancer. Thus, there is a search for radical scavenging agents capable of circumventing oxidative stress. Due to their remarkable properties, quantum dots are known to be utilized in a variety of applications including binding of reactive oxygen species (ROS). However, the translation of nanomaterials to clinic is often hampered by their off target toxicity. Thus, the aim of our work is to develop and test fully biocompatible graphene quantum dots (GQDs) with a variety of dopants that will the tune radical scavenging activity (RSA) of the GQD. We have synthesized and tested over ten types of doped GQDs and accessed their radical scavenging ability via DPPH, KMnO4, and RHB assays. Among those, thulium and aluminum doped GQDs show superior scavenging.

Respiratory syncytial virus (RSV) can cause a severe respiratory illnesses particularly in young children and the elderly. Defective viral genomes (DVGs) have recently been found during RSV infections and are thought to be linked to the severity of the illness. In this study, we use mathematical models to simulate the spread of RSV using data from environments in which DVGs are detected early and late in order to estimate infection rates and other infection parameters in each setting. We find that the presence of DVGs is reflected in changes in the infection rate and viral clearance rate of infections.

During the first billion years after the Big Bang the first, faint, galaxies formed. With luminosities less than one millionth that of our Milky Way galaxy, they are too faint to be observed by even our most advanced telescopes. A fraction of these first galaxies are preserved as ultra-faint dwarf galaxies in the local universe. These ultra-faint dwarfs are the fossils of the first galaxies. Therefore, we can study the faintest satellites of the Milky Way and learn about the formation and evolution of the first galaxies using galactic paleontology. We know that the stellar properties of the faintest Milky Way satellites match the stellar properties of galaxies formed in high resolution hydrodynamic simulations of the first billion years. We also know that the semi-analytic model Galacticus can reproduce the stellar properties of the faintest Milky Way dwarfs in the modern epoch. In this work, we determine whether Galacticus is also able to match the high resolution simulations of the first billion years.

The creation and evolution of elements throughout time across the Milky Way disk provides a key constraint for galaxy evolution models. To provide these constraints, we are conducting an investigation of the zirconium, neodymium, cerium, and barium abundances created in supernovae explosions, for a large sample of open clusters. The stars in our study were identified as cluster members by the Open Cluster Chemical Abundance & Mapping (OCCAM) survey that culls member candidates by Doppler velocity, metallicity, and proper motion. We have obtained new data for the elemental abundances in these clusters using the Subaru Observatory 8-m telescope in Hawaii with the High Dispersion Spectrograph (HDS). Analyzing these neutron-capture abundances in star clusters will lead us to new insight on star formation processes and the chemical evolution of the Milky Way galaxy.

Cancer is a leading cause of death worldwide with around one in every six caused by cancer, but many cancers can be cured if treated properly. Mathematically programmed cancer cell models can be used by researchers to study the use of oncolytic viruses to treat tumors. With these models, we are able to help predict the viral characteristics needed in order for a virus to effectively kill a tumor. Our approach uses both cancerous and non cancerous cells in relationship to the tumor to determine the speed at which the cells replicate, however there are several models used to describe cancer growth, including the Exponential, Mendelsohn, Logistic, Linear, Surface, Gompertz, and Bertalanffy. We study how the choice of a particular model affects the predicted outcome of treatment.

The first galaxies formed 12.5 billion years ago during the first billion years after the Big Bang. However, these first, faint, galaxies remain too faint for direct detection, even by our most powerful telescopes. Therefore we study them using their fossils relics, ultra-faint dwarf galaxies orbiting the Milky Way. In this work, we look at the histories of star formation in simulated analogs to the ultra-faint dwarfs. These star formation histories will allow us to study the details of how and when star formation occurred during the first billion years of cosmic time. We are particularly interested in how massive the first galaxies were when they formed the majority of their stars.

Coinfection affects up to 60% of patients hospitalized influenza-like illnesses, however, the role of the innate immune response in coinfections is not understood. Interferons, part of the innate immune response, are a type of chemical released by infected cells that can help establish an antiviral state in cells by increasing resistance to infection and reducing production of viruses. Although the increased resistance to infection can help suppress both viruses, the reduction in the production of one virus may aid in increasing the growth of another virus during coinfection due to less competition. We will use a mathematical model to examine the interaction via interferons between respiratory syncytial virus (RSV) and influenza A virus (IAV) during coinfections. This model will measure viral titer, duration of the viral infection, and interferon production allowing us to understand how interferon production of one virus helps or hinders the secondary virus.

Due to the enormity of different forms of cancer and the increase in cancer rates globally, it is essential to continually develop more advanced methods of early and localized detection of cancer cells, as well as methods of targeted drug delivery. As a result, a vast amount of research has gone into the use of nano-materials such as graphene quantum dots (GQDs) as the basis for a wide variety of biomedical sensing and treatment applications. While many diagnostic biomarkers have been detected using modified GQDs, one biomarker that has not yet been successfully detected or targeted using GQDs is Transgelin-2. Transgelin-2 is a unique actin-binding protein that has been projected to be a useful biomarker and target of treatment for many different forms of cancer, as well as asthma and immune diseases such as lupus. Herein I review the structure of the Transgelin-2 protein, novel methods of GQD modification to sense cell membrane surface proteins, and ultimately determine the viability of GQDs as a method for detecting and targeting Transgelin-2. Furthermore, I develop a possible methodology by which these biophysical applications may be tested.

Antimicrobial action of micro- and nanoscale ZnO particles has been documented, but the fundamental physical mechanisms driving these actions are still not identified. We hypothesize that one of the key mechanisms behind the antibacterial action of ZnO is rooted in interactions between ZnO surfaces and extracellular material. An investigation was done of the biological components of that interaction using diffusion theory and more specifically Brownian motion computational models to look at the interaction of Zn+2 and O-2 ions with staphylococcus aureus bacteria. The analysis allowed us to find a correlation between the thickness of the staphylococcus aureus bacteria and the amount of the zinc and oxygen ions present in the solution.

Nano- and microscale zinc oxide (ZnO) have demonstrated potential for applications in electronic, pharmacological and chemical industries among others. At these scales, surface properties dominate, rendering surface defects highly influential. Consequently, understanding of defect- related phenomena are crucial to achieving impactful figures of merit. Many optoelectronic properties of ZnO relevant for applications have been linked to defect-related visible luminescence. Its fundamental origins are still being debated, with attributions to oxygen vacancies, zinc vacancies, oxygen antisites, donor-acceptor pairs, etc. In our studies, we contribute to this discussion by probing the relationship between crystal morphology and this luminescence. We conducted optoelectronic studies to characterize the effects of remote oxygen plasma treatment on hydrothermally-grown microscale ZnO samples with controlled morphology as a means to help elucidate the nature of the visible emission. We report on the observed changes in the photoluminescence spectra indicative of the relationship between surface defects, morphology, and electronic structure of ZnO.