Oral health is an essential part of overall well-being, yet many children in underserved communities lack access to dental education and basic hygiene resources. Although cavities are completely preventable, they remain one of the most common chronic diseases affecting both children and adults. Early education is crucial for building lifelong habits and preventing future dental issues. The New Smiles initiative is a student-led outreach program focused on improving oral hygiene awareness and access to care among elementary students in the Fort Worth community.

Through interactive elementary school presentations, the program teaches proper brushing and flossing, healthy eating habits, and the importance of routine dental visits to kids. To reinforce these lessons, hygiene kits containing toothbrushes, toothpaste, floss, and educational materials were assembled in collaboration with Cook Children’s and distributed to participating students. Additionally, a brief survey was administered to assess students’ baseline knowledge of oral hygiene and evaluate the effectiveness of the educational presentation.

By combining hands-on education, community partnerships, and the distribution of essential hygiene supplies, the New Smiles program aims to promote preventive oral health practices at an early age. This initiative seeks to reduce oral health disparities while empowering children with the knowledge and resources needed to maintain lifelong dental health.

Women who are obese have a much higher risk of being diagnosed with breast cancer than women who maintain a healthy body weight. However, excess body fat, even in the absence of excess body weight, a condition referred to as normal weight obesity also increases breast cancer risk. The goal of our study is to determine how serum from human subjects with three distinct obesity phenotypes, metabolically healthy obese, metabolically unhealthy obese, and normal-weight obese, influences breast cancer cell growth and proliferation. We have already collected preliminary data indicating differences in cell viability via NADH measurement, yet metabolic activity alone does not definitively demonstrate growth or vitality because cells may be metabolically active without entering S-phase or replicating. To conclusively show DNA replication (and thus true proliferation/vitality), our plan is to quantitatively measure differences in DNA synthesis using the Click-iT EdU DNA-synthesis assay, which uses a thymidine analog incorporated into newly synthesized DNA which can be detected by the appearance of fluorescent conjugates. Based on our preliminary findings, we expect that the lower rates of metabolic activity in cells grown in serum from obese subjects are not due to reduced rates of cellular proliferation. These findings could be used to inform improved, targeted nutritional and chemotherapeutic strategies for individuals with distinct obesity phenotypes.

Viral stability, replication, and host-virus interactions are all significantly impacted by temperature. Numerous experimental studies have demonstrated that SARS-CoV-2 grows differently at different temperatures, but it is still unknown which specific infection processes are impacted. In this work, we used a mathematical modeling approach to quantify the effects of temperature on the kinetic parameters controlling SARS-CoV-2 replication. Results from previously published experiments were used to determine the viral load from in vitro infections of Vero E6 and human nasal epithelial (hNEC) cells at 33 and 37 C. We fit a mathematical model of viral infections to estimate model parameters at the two temperatures. Vero E6 cells showed evidence of temperature dependence when parameter distributions were compared; the infection rate, eclipse phase transition rate, and infected cell death rate varied between 33 and 37 C. The parameter estimates in hNEC cells, on the other hand, revealed no statistically significant differences and showed a significant overlap in parameter estimates between temperatures. These results imply that the cellular environment has a significant impact on how temperature affects SARS-CoV-2 replication dynamics. The measurement of temperature-dependent variations in viral kinetic parameters sheds light on SARS-CoV-2 replication and could enhance forecasts of infection dynamics under various environmental and physiological circumstances.

Our Milky Way’s neighbor, the Large Magellanic Cloud (LMC), is a galaxy significantly shaped by powerful explosions from massive, dying stars that drive gas outflows. These explosions release gas and heavy elements, enriching the galaxy's outskirts and contributing to the formation of stars and planets. Understanding these processes is crucial for studying galactic evolution and the mechanisms that drive it. Our research uses observations from the Hubble Space Telescope to characterize the properties of the outflows from the LMC. Our observations are of light from background stars that pass through the LMC’s gas clouds. These clouds block some of the incoming light, and we analyze the missing features to study the physical properties of the outflows. To compare complex stellar spectra on a similar scale, we fit regions of the light that are free from major features blocking it with a best-fit polynomial. This process helps us differentiate components that either belong to the background star or the LMC’s outflowing gas. By examining the missing light, we gain a deeper understanding of how bursts of star formation impact the galactic environment and ultimately connect our existence to the explosive deaths of distant stars.

Zinc oxide (ZnO) is a versatile, inexpensive semiconductor material with unique characteristics. ZnO is particularly known for its inhibitory effects on bacterial growth. ZnO can reduce bacterial growth through mechanisms such as oxidative stress, the deterioration of crucial proteins in the bacterial cell, and the release of Zn²⁺ ions that affect bacterial cell function. The exact mechanism behind ZnO’s antibacterial properties remains unclear. It has been seen that changing the surface and morphology of the particles changes their effectiveness for bacterial inhibition. An additional lesser explored branch of ethanol-based synthesis is solution pH pertaining to ZnO morphology. Our research aims to explore this by doing a wholistic investigation of an ethanol-based synthesis, especially pertaining to how pH affects particle morphology. To produce these materials, we used ethanol-based solvothermal synthesis to create ZnO micro- and nanocrystals. We performed a thorough characterization of these materials to observe changes to the ZnO lattice. This was done by employing scanning electron microscopy (SEM), energy-dispersive X-ray (EDX) spectroscopy, and X-ray diffraction (XRD) spectroscopy.

Graphene quantum dots GQDs possess broad potential in bioimaging and optoelectronics due to their unique optical properties, tunable structure, aqueous solubility, and minimal in vivo and in vitro toxicity. However, despite their solubility, GQD fluorescence may be quenched through interactions with water molecules and aggregation via non radiative decay pathways that reduce emission efficiency. Inspired by the ability of surfactants to prevent quenching interactions for single walled carbon nanotubes, we investigate their utility in preserving GQD fluorescence. Five structurally distinct surfactants, sodium dodecyl sulfate SDS, sodium dodecylbenzene sulfonate SDBS, sodium deoxycholate SDC, sodium cholate SC, and Pluronic F127, are tested across a range of concentrations for preserving fluorescence of top down and bottom up synthesized GQDs to determine optimal conditions. This work reveals that surfactant structure and concentration can non-linearly affect GQD emission in the visible and near-infrared, with SC and SDC providing maximum concentration dependent fluorescence increase. Zeta potential and dynamic light scattering measurements are conducted for each surfactant and GQD system to quantify interfacial charge, colloidal stability, and aggregate size distributions. The present study provides mechanistic understanding of how surfactants influence GQD photophysics, offering strategies to optimize GQD based probes for biomedical imaging and photonic applications establishing a structure-to-function framework that links solution phase organization to fluorescence emission.

Graphene quantum dots (GQDs) have gained significant attention due to their unique optical properties, biocompatibility, and potential applications in bioimaging, biosensing, and optoelectronics. The breakdown of single-walled carbon nanotubes provides an alternative method of producing GQDs that has the potential to be more efficient than current methods. We will investigate the effectiveness of various methods to break down single-walled carbon nanotubes, including through UV-light irradiation. Solutions of carbon nanotubes with sodium hypochlorite are placed under 254nm UV-light for two hours, and fluorescence in the visible spectrum is measured before and after UV-light irradiation to observe the production of GQDs. The use of surfactants in these solutions can affect the resulting fluorescence, so solutions of sodium dodecyl sulfate (SDS) and sodium dodecylbenzene sulfonate (SDBS) are also UV-light irradiated and observed. We will perform transmission electron microscopy (TEM) analysis on the samples to characterize the resulting GQDs and determine their size distribution. The findings from this study will contribute to the broader scientific community by improving an avenue of production for GQDs through conversion of carbon nanotubes into smaller, more functional materials while reducing the toxicity associated with carbon nanotubes.

Defective interfering particles (DIPs) are virions missing the viral genome that allows them to replicate on their own, so they require coinfection with a standard virion to enable replication, interfering with the production of standard virus in the process. DIPs may also stimulate an interferon (IFN) response that further suppresses standard virus replication. Our aim was to evaluate the impact of DIPs and IFN on viral replication. We used Python programming to simulate a mathematical model evaluating the effects of DIPs and IFN on viral replication. Features of the viral titer curve were measured, including peak viral load and area under the viral curve, as functions of IFN parameters and DIP production rates. We examined a range of parameter values for DIP production rate and IFN response strength to assess the effects of DIPs and IFN independently and together. DIP production rate over a range of values resulted in no change in DIP or standard virus population dynamics. However, decreased IFN response resulted in an increase in standard virus and DIP population, while increased IFN response resulted in decreased standard virus and DIP population. DIP production in isolation did not impact viral replication, while IFN demonstrated an inverse relationship to viral replication and DIP production. Increased IFN and DIP production rate led to a reduction in infection intensity. IFN is essential to the antiviral effects of DIPs.

Galaxy simulations are an effective way to study the evolution of galaxies across
cosmic time. They have provided insights into the structural and chemical evolution
of galaxies, gas and star formation, and how LCDM models predict the large scale
structure of universe. Nevertheless, two primary issues have persisted using LCDM -
the core-cusp problem and the diversity of rotation curves for dwarf galaxies of similar
masses. To determine the effect of AGN on these issues, we utilize FIRE-2, which only
includes stellar feedback. We chose this particular galaxy at redshift 0 and compared
the curve to 8 previous observations, and we find that the innermost regions of the
curve are better matched to the data, but diversity still remains a problem. Thus, we
conclude that AGN feedback prescriptions may be removing too much mass from the
center of the galaxy, causing this discrepancy. Hence, more work is necessary to identify
the cause of this issue and potentially resolve it.

Influenza virus causes periodic pandemics and thousands of deaths annually, but many of the details of the viral replication cycle are still poorly understood. This study develops a mathematical model of the dynamic transitions of a virus from the extracellular space through the initial intracellular replication processes. These stages include: binding, endocytosis, HA Acidification, Fusion, and Uncoating. Experimental data from the viral entry phases were fit to a system of differential equations, which represent the biological processes. The model parameters were estimated using optimization techniques that minimize the sum of squared residuals, thereby aligning model predictions with observations. An identifiability analysis was performed to see which parameters can be estimated with the given model and available data. We find that the model fits the experimental data well with identifiable parameters, allowing us to characterize the different stages of viral entry. The model can be used to compare different viral strains or treatment options, in addition to helping explain the kinetics of viral entry.