Historically, students have envisioned scientists as white males in lab coats, reinforcing exclusionary stereotypes that can discourage diverse participation in STEM. Mentorship has the potential to broaden perspectives, enhance self-esteem, and support identity development, yet research on its specific impact in middle school remains limited. This study examines how a structured mentorship program influences middle school students’ perceptions of scientists and their own scientific identity, particularly in STEM and healthcare professions, asking: How does mentees’ identity in science and healthcare professions develop through interactions with mentors and peers? This qualitative study follows seven 7th- and 8th-grade students (ages 13–14) in a year-long mentorship program led by junior college undergraduates. The research employs a pre- and post-intervention assessment using the Draw-a-Scientist Test (DAST) alongside open discussions and interviews to evaluate shifts in students’ identity perceptions. DAST drawings are analyzed with a rubric evaluating gender, activity, location, and skin tone to identify shifts toward more inclusive representations. The study anticipates that students will depict more diverse scientists over time, moving beyond traditional stereotypes. Findings are expected to reveal more diverse depictions of scientists, offering insights into how mentorship fosters inclusivity and belonging in STEM for underrepresented middle schoolers. 

Crafts and Conversations collaborates with Trinity Terrace and Brookdale assisted living facilities to foster a connection between TCU students and the residents living there. Through monthly meet ups with crafts and music, inter-generational relationships are built between students and residents. Crafts such as painting with mini easels or making yarn octopi provide a base talking point that expands into other natural parts of conversation, such as telling stories. Students that volunteer at crafts gain friendships, valuable interactions that combat stereotypes against the elderly, and improved communication skills. Additionally, students have the opportunity to perform music, enabling them to further expand their creativity. Residents at assisted living facilities also gain valuable friendships and interactions that combat the potential loneliness of at a retirement center. Crafts and Conversations strives to enrich the lives of all those involved through engaging activities that bring people closer together.

Beautiful Feet Clinic, founded by Dr. David Capper, provides free medical, dental, and holistic care for individuals experiencing homelessness in Southside Fort Worth. One of the critical challenges faced by individuals experiencing homelessness is the lack of access to preventive screenings, flu vaccinations, and health education, leading to the late detection of chronic illnesses such as diabetes, hypertension, and cancer. Many patients at Beautiful Feet Clinic do not routinely engage in preventive care, as their immediate survival needs—such as securing food and shelter—often take precedence over long-term health maintenance. Without timely interventions, undiagnosed and unmanaged chronic illnesses contribute to higher emergency department utilization, increased morbidity, and worsening overall health outcomes.

To address this gap, we partnered with Lauren, a medical student at TCOM, to offer flu vaccinations and organize a Community Health Screening Day on March 29th, 2025, offering essential health screenings and practical nutrition education aimed at empowering individuals experiencing homelessness to improve chronic disease management and overall well-being. Patients will learn simple meal modifications to make healthier choices within their available food options through educational pamphlets with a focus on nutritional education to reduce chronic illnesses. The event also enhances medical student training, with efforts to secure an OB-GYN physician to guide manual breast exams and oversee preventive education regarding breast and skin cancer screenings. The initiative also administered 22 flu vaccinations to address gaps in preventive care, reducing the risk of seasonal influenza among unhoused individuals who face significant healthcare barriers. Additionally, in collaboration with Moncrief Cancer Institute, a mobile cancer screening clinic, we will provide free cancer screenings in summer 2025, to promote early detection for at-risk individuals.

Beyond medical care, Beautiful Feet Clinic also faces communication barriers with Spanish-speaking patients, limiting access to critical health services. Many patients and healthcare providers recognize the need for language accessibility and the importance of qualified interpreters in delivering effective care. To address this, we translated the clinic’s intake forms into Spanish and established a list of medical students proficient in Spanish who can assist with interpretation over the phone. This initiative enhances provider-patient communication, ensuring that Spanish-speaking individuals receive accurate medical information and compassionate care.

By integrating screenings, outreach, language accessibility, and hands-on clinical training, this initiative fosters health empowerment and long-term community-based healthcare solutions. It emphasizes collaboration between healthcare institutions, students, and local clinics to bridge gaps in care for vulnerable populations.

Geodesic nets are types of graphs in Riemannian manifolds where each edge is a geodesic segment. One important object used in the construction of geodesic nets is a balanced vertex, where the sum of unit tangent vectors along adjacent edges is zero. We prove the existence of a balanced vertex of a triangle (with three unbalanced vertices) on a general two-dimensional Riemannian surface when all angles measure less than $2\pi/3$, if the length of the sides of the triangle is not too large. This property is a generalization for the existence of the Fermat point of a planar triangle.

The Cheeger’s constant, also known as the isoperimetric number, is a constant that helps describe the bottleneck present in a graph, if any. Some fields, such as computer networks, have an interest in this constant due to the application of the constant in their field. We examined randomly generated connected graphs and their isoperimetric numbers by developing algorithms to calculate it.

One of the major challenges in education is accurately quantifying a student’s knowledge and skills. Since we cannot directly measure a student’s true intelligence, we rely on test performance, which serves as an imperfect representation of their abilities. This issue arises in many statistical applications where the key problem involves a population in which each individual possesses an underlying ability or trait that cannot be directly observed but can only be inferred through proxy variables. However, these proxies are often contaminated, providing only a noisy or imperfect approximation of the true latent variable.
This project focuses on techniques for recovering latent variables from noisy data. In this context, "recovery" refers to estimating the latent variable using indirect observations. Assuming a linear relationship between the latent trait and the observed proxy variables, we can estimate model parameters and subsequently recover the values of the latent variables.
Specifically, we will examine statistical approaches to latent variable recovery when the test contains items that exhibit differential item functioning (DIF). This means that certain test items do not solely measure the intended knowledge or ability but are also biased toward specific groups. The objective is to develop methods that detect the presence of DIF and adjust for it, allowing for a more accurate estimation of the underlying abilities.
To illustrate these methods, we will use the Holzinger-Swineford dataset, a well-known dataset in psychometrics used to analyze cognitive abilities across multiple domains. This dataset includes 88 observations with scores in five areas: Mechanical Comprehension, Verbal or Visual Comprehension, Algebra Operations, Analytical Operations, and Statistical Reasoning. By applying a linear contamination model, we aim to recover each student's latent ability while accounting for DIF.

Oral Reading Accuracy (ORA) is an important metric for evaluating a student's reading proficiency, measuring how accurately a reader can read words aloud. Traditional ORA evaluations performed by human assessors often require significant time and labor. This study explores the potential of integrating a speech recognition system into ORA assessments to improve efficiency. We analyzed ORA data from 507 elementary school students across ten passages of different lengths and difficulties. Both human evaluators and AI systems recorded the number of words read correctly. The misclassification rates of these scores are divided into two components: True Positive (correct words are identified as correct), and True Negative (incorrect words are identified as correct). This second study expands upon Method of Moments method to estimate these misclassification rates. We apply Generalized Method of Moments which incorporates additional variance information. To compare the two approaches' accuracy, we apply the m-out-of-n Bootstrap method to estimate their standard errors and compare their reductions in estimator variance. Additionally, we introduce a Contaminated Data Solution to address real-world scenarios where true count data is unavailable and only contaminated observed data is observed.

Sepsis-induced acute kidney injury (S-AKI) is a critical illness that causes decreased kidney function due to infection. With a prevalence of 40-50% of patients in the intensive care unit developing S-AKI, the illness is strongly associated with a higher risk of mortality, longer hospital stays, and increased risk of kidney failure relapse. S-AKI complicates medical nutrition therapy due to altered protein metabolism, increased metabolic demands, fluid imbalances, increased malnutrition risk, and electrolyte imbalances. Goals of nutrition care include close monitoring and evaluation of fluid, meeting estimated protein needs, maintaining electrolyte and vitamin status, and achieving supplemental nutrition tolerance to optimize kidney recovery and prevent malnutrition. Various nutrition interventions, such as individualized protein needs and enteral nutrition (EN), play a role in managing this illness. Evidence-based guidelines for protein recommendations vary based on the type of renal replacement therapy (RRT) and range from 1.2-2.5 g/kg/day. Patients with declining renal function prior to RRT and at risk for chronic kidney disease have a range of 0.8-1.0 g/kg/day to preserve long-term kidney function. Literature indicates initiation of EN within 24 hours is preferred over parenteral nutrition (PN) if oral intake is not feasible to prevent malnutrition. While there are no standardized fluid intake guidelines for S-AKI, continuous multidisciplinary assessment and adjustment to fluid intake are necessary to prevent volume overload. This case report reviews the importance of proactive individualized nutrition interventions to aid in patient recovery including improved nutritional status and AKI resolution.

Background: Research in animals and humans indicate that the gut microbiome plays a significant role in modulating insulin resistance1,2, while animal studies have demonstrated the gut microbiome's direct involvement in regulating body weight3,4. Furthermore, antibiotic use may impair insulin sensitivity and glucose tolerance in individuals with overweight and obesity5-9. However, no studies to date have evaluated the potential factors influencing this metabolic response.

Methods: This is a randomized clinical trial with a within- and between-subjects comparison. Seventy-five individuals aged 18-50 years (BMI 25.0-40.0 kg/m2), with no Diabetes Mellitus diagnosis, and no recent probiotic or antibiotic intake (3 months) were recruited. Participants were allocated to a synbiotic or placebo group for 12 weeks following a 3-day Vancomycin antibiotic intervention (500 mg every 8 hours). Body weight and fasting blood samples (glucose, insulin, HbA1c) were taken at the first (baseline), second (after antibiotic administration), and third visit (after synbiotic/placebo intervention). HOMA-IR was calculated from fasting insulin and glucose levels. Due to lack of normal distribution of independent variables, Mann-Whitney U tests were performed to evaluate within- and between-group changes over time.

Results: Compiled results for all participants were analyzed, although only 60 completed the study. It is important to highlight that the placebo group was significantly heavier at baseline (91.8 ± 18.1 kg) than the synbiotic group (82.8 ± 14.3 kg) (p=0.046), while the latter had a modest weight gain over time (~0.80 kg, p=.056). Neither fasting glucose nor HbA1C changed significantly between groups over time. HbA1c, insulin, and HOMA-IR slightly increased from baseline in all participants (p<.001 each), which could indicate a decreased insulin sensitivity over time, with no significant differences between groups.

Conclusion: Our unadjusted analysis demonstrates that providing a 12-week next-generation synbiotic supplementation posterior to a 3-day antibiotic intervention did not correct the commonly observed detrimental effect of antibiotics on insulin resistance. Furthermore, it seemed to lead to significant weight gain (~0.80 kg, p=.056).

Implications for future research: We are planning on re-running all our statistical analyses controlling for baseline sex and we are also planning on running an independent third group with antibiotics only for comparison purposes.

Funding Source: Pendulum® and TCU Dean’s Opportunity Grant

References
1. Sergeev IN, Aljutaily T, Walton G, Huarte E. Effects of Synbiotic Supplement on Human Gut Microbiota, Body Composition and Weight Loss in Obesity. Nutrients. Jan 15 2020;12(1)doi:10.3390/nu12010222
2. Wu Z, Zhang B, Chen F, et al. Fecal microbiota transplantation reverses insulin resistance in type 2 diabetes: A randomized, controlled, prospective study. Front Cell Infect Microbiol. 2022;12:1089991. doi:10.3389/fcimb.2022.1089991
3. Ridaura VK, Faith JJ, Rey FE, et al. Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science. Sep 6 2013;341(6150):1241214. doi:10.1126/science.1241214
4. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER, Gordon JI. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature. Dec 21 2006;444(7122):1027-31. doi:10.1038/nature05414
5. Del Fiol FS, Balcão VM, Barberato-Fillho S, Lopes LC, Bergamaschi CC. Obesity: A New Adverse Effect of Antibiotics? Front Pharmacol. 2018;9:1408. doi:10.3389/fphar.2018.01408
6. Klancic T, Laforest-Lapointe I, Wong J, et al. Concurrent Prebiotic Intake Reverses Insulin Resistance Induced by Early-Life Pulsed Antibiotic in Rats. Biomedicines. Jan 12 2021;9(1)doi:10.3390/biomedicines9010066
7. Park SJ, Park YJ, Chang J, et al. Association between antibiotics use and diabetes incidence in a nationally representative retrospective cohort among Koreans. Sci Rep. Nov 4 2021;11(1):21681. doi:10.1038/s41598-021-01125-5
8. Yuan J, Hu YJ, Zheng J, et al. Long-term use of antibiotics and risk of type 2 diabetes in women: a prospective cohort study. Int J Epidemiol. Oct 1 2020;49(5):1572-1581. doi:10.1093/ije/dyaa122
9. Zhou J, Lin Y, Liu Y, Chen K. Antibiotic exposure and risk of type 2 diabetes mellitus: a systematic review and meta-analysis. Environ Sci Pollut Res Int. Dec 2021;28(46):65052-65061. doi:10.1007/s11356-021-16781-3

Medical nutrition therapy is necessary for individuals at risk of impaired wound healing, such as those with malnutrition, poor circulation, or advanced age. During the acute inflammatory response from wounds, the body enters a catabolic state, increasing energy and protein needs. For those with malnutrition or at risk for malnutrition, calories should be provided at 30-35 kcal/kg body weight and protein at 1.25-1.5 g/kg body weight. Along with increased energy needs, the assessment and management of vitamins and minerals such as vitamins A, vitamin C, vitamin K, and zinc enhance the synthesis of fibroblasts needed for tissue formation. Early diagnosis and intervention for malnourished patients with chronic wounds are critical steps in providing effective patient care. Oral intake is monitored to ensure calorie and protein intake is adequate and oral nutrition supplements may be provided if indicated. For those unable to tolerate oral feeds, enteral nutrition is the next preferred method. If enteral nutrition is contraindicated then parenteral nutrition can be initiated to provide adequate calories and protein. This case report analyzes the care of a 74-year-old female with a non-healing surgical wound with a history of bariatric surgery who has been diagnosed with malnutrition.

Essential fatty acid deficiency (EFAD) is a condition that can occur when the body does not have adequate fats from the diet. EFAD can develop in as quick as 10 days and can present with symptoms such as itchy and flaky skin, poor wound healing, elevated liver function tests, and increased susceptibility to infection. EFAD rarely occurs in individuals who eat a balanced diet with a variety of foods and fat sources and is seen most often in patients unable to eat by mouth or tolerate tube feedings. Patients with prolonged poor nutrition are at increased risk of EFAD due to insufficient fat intake. Risk factors of EFAD are inflammatory bowel disease, pancreatic insufficiency, extreme diet restriction, and long-term parenteral nutrition support with limited fat emulsion supplementation. Preventing EFAD through awareness and proactive measures is essential in medical nutrition therapy. Since clinical markers are challenging to assess in the acute care setting, physical signs and symptoms are used for identifying and treating EFAD. For patients on parenteral nutrition support with no fat, supplementing with 500 mL intralipids per week is recommended to prevent EFAD. This case report reviews the current nutritional guidelines related to EFAD and parenteral nutrition and highlights a patient at risk for EFAD due to her poor intake, who was receiving long-term parenteral nutrition with supplemental oral intake.

Necrotizing pancreatitis is a severe acute inflammation of the pancreas that disrupts the release of pancreatic enzymes necessary for digestion and the production of insulin needed to stabilize blood glucose levels. Common complications associated with necrotizing pancreatitis include diet intolerance, abdominal pain, nausea, vomiting, decreased oral intake, and hyperglycemia. If the patient cannot meet their estimated nutritional requirements via an oral diet, supplemental nutrition support, such as enteral nutrition (EN) through a feeding tube or parenteral nutrition intravenously through a peripheral or central line, must be considered to prevent malnutrition. When necessary, early initiation of supplemental nutrition support within 24-48 hours of admission is associated with shorter hospital stays. To improve diet tolerance and reduce symptoms while utilizing EN, patients with necrotizing pancreatitis may be fed elemental or semi-elemental formulas through a feeding tube placed in a post-pyloric position. Additionally, insulin therapy may be utilized in cases where patients experience hyperglycemia due to exocrine pancreatic insufficiency. The target blood glucose range for hospitalized patients is less than 180 mg/dL, or less than 140 mg/dL if there is no significant risk of hypoglycemia. Insulin therapy should be initiated when a patient experiences a blood glucose level greater than or equal to 180 mg/dL at least twice within a 24-hour period. This case report evaluates the management of EN intolerance and hyperglycemia when treating individuals with necrotizing pancreatitis.

Decompensated alcoholic cirrhosis is failure of the liver due to alcohol use, accompanied by complications such as portal hypertension, bleeding varices, ascites, and encephalopathy. Nutrition is vital in managing cirrhosis as the loss of hepatocytes from liver damage impairs gluconeogenesis, causing the body to use amino acids and fatty acids for energy, thereby increasing resting energy expenditure. Malnutrition is often diagnosed in patients with decompensated cirrhosis due to increased nutrition needs and comorbidities like altered mental status and ascites, which cause early satiety and negatively affect oral intake. Therefore, nutrition interventions to treat or prevent malnutrition are essential. Evidence indicates cirrhotic patients are at risk for malnutrition should eat three to five meals plus snacks to shorten fasting periods. If calorie and protein needs cannot be met through oral intake, initiating enteral nutrition may be appropriate. Enteral nutrition is preferred unless it is contraindicated, in which case parenteral nutrition would be utilized. Nocturnal enteral feeds may be permissible to shorten fasting periods if oral intake is tolerated but intake does not meet nutritional needs. Nutrient recommendation ranges for cirrhotic patients are 35 calories per kilogram and 1-2 grams of protein per kilogram, based on actual or estimated body weight. Vitamin and mineral supplementation may be needed for patients with a history of alcohol abuse, specifically thiamin, niacin, folate, magnesium, and zinc. This case report explores the complex nutrition needs and goals of care in a patient with decompensated alcoholic cirrhosis and severe chronic protein-calorie malnutrition.

Ga2O3, an ultrawide-bandgap semiconducting material, sees widespread use in optoelectronic, pharmaceutical, and other industrial applications. Additionally, as antibiotic resistance grows, interest rises in the antibacterial properties of Ga2O3 and other gallium-containing compounds. In many cases, GaOOH is a precursor to synthesis of Ga2O3 with similar physiochemical properties. For microparticles, surface effects become heavily amplified. In particular, the surface effects may significantly influence antibacterial action. We synthesize GaOOH and Ga2O3 microparticles via hydrothermal growth. We employ scanning electron microscopy to image samples and energy dispersive X-ray spectroscopy to characterize the stoichiometry. X-ray diffraction spectroscopy is used by us to monitor bulk structural differences between the GaOOH precursor and Ga2O3. To monitor crystal defects we utilize photoluminescence spectroscopy. For antibacterial assays, we test our materials against Staphylococcus aureus bacteria using optical density measurement at 600 nm.

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.

Graphene Quantum Dots (GQDs) are nanoscale carbon based graphene sheets that exhibit unique fluorescent properties throughout a wide range of wavelengths. Given their uniquely small size, low toxicity, biocompatibility, and fluorescent capabilities, GQDs have many unique and important roles. To name a few, GQDs are used in drug delivery, fluorescent imaging, and biosensing thanks to their unique ability to fluoresce under different wavelengths of light. Furthermore, there are different types of GQDs with their own unique properties. Knowing this, five amphipathic molecules, called surfactants, were added to two different types of GQDs to test if they would impact the resulting fluorescence. Furthermore, concentrations of these added surfactants were varied to test how different concentrations of a given surfactant might affect the fluorescence for a given GQD. We observed that some of these surfactants provided a beneficial boost to GQDs fluorescence, while others slightly inhibited the fluorescence. Moreover, we saw that the increase in fluorescence varied based on the concentration of surfactant added yielding lower fluorescence for extremely low and high concentrations, while increasing the fluorescence at a more moderate concentration.

With cancer rates increasing at an alarming rate, many traditional methods for cancer treatment begin to feel outdated. This is where engineering nanomaterials, such as Graphene Quantum Dots (GQDs), offer a promising approach to making chemotherapy a more targeted treatment and therefore minimizing the side effects. This study focuses on optimizing drug delivery mechanisms using GQDs, specifically Reduced Graphene Quantum Dots (RGQDs) synthesized via a top-down approach from reduced graphene oxide, and Hyaluronic Acid Graphene Quantum Dots (HAGQDs) synthesized bottom-up from hyaluronic acid. The process is done by loading chemotherapeutics Gemcitabine, Paclitaxel, and Doxorubicin (DOX) HCl onto GQDs through sonication, this is followed by a centrifugal purification which isolates properly drug-loaded GQDs. To evaluate their controlled release, photothermal properties of GQDs are utilized. Samples are excited with an 808 nm laser at 1, 5, and 10 minutes, and they are later compared to a control group. This analysis provides insights into how laser stimulation affects drug release efficiency, paving the way for advancements in GQD based cancer treatments.

We introduce a structural method used for quantifying the spatial heterogeneity(or clumpiness) of viral syncytial cells in a transfection 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.

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.

Our neighboring galaxies, the Large Magellanic Cloud (LMC) and Small Magellanic Cloud (SMC), interact with each other as they move through the hot, outer region of the Milky Way. This interaction can pull and sweep away gas from the edges of the galaxies, forming large, stretched-out clouds of gas. The LMC has two gas filaments that resemble arms, which connect to a region where stars are formed, possibly hinting toward their origin or their final destination. In this study, we used radio observations and data from the Hubble Space Telescope to search for signs of these gas arms near the star-forming region. We find a continuous stream of gas that could be the arms located at least partially in front of the LMC. The positioning of these arms raises two competing questions: 1) Is the gas flow fueling new star formation in the LMC, or 2) Is gas from exploded stars in the LMC flowing out into these arms? While the inflow of gas makes sense for these gas flows, we also conducted simulations of outflows from the starburst region. Our results suggest that it is possible for debris from exploded stars to be swept into the arms. Future observations will help us better reconstruct the arms’ evolutionary history.

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.

After the COVID-19 pandemic, over 40 million children worldwide are at risk of measles due to delayed vaccination and temporary SARS-CoV-2 viral dominance. The lasting immunosuppression caused by the disease presents a major health threat, and treatment options are urgently needed, especially for low- and middle-income countries. The manuscript by Cox et al. (2024) explores features of canine distemper virus (CDV) in ferrets, using this model as a surrogate for measles to evaluate two possible antiviral treatments, ERDRP-0519 and GHP-88309. Ferrets were infected with a lethal challenge of CDV and treated with either drug or therapeutic vaccination. We aim to characterize both the infection dynamics and efficacy of the two drug treatments using the data from the PBMC (peripheral blood mononuclear cell) associated viremia titers of CDV infected ferrets and the lymphocyte counts measured during the duration of the study. A differential mathematical model was fitted to the experimental data by minimizing the sum of squared residuals (SSR), and errors in the parameter fits were estimated using Monte Carlo Markov Chain (MCMC). We visualized the key parameter distributions for each dataset using histograms, allowing us to directly compare how each treatment influences infection dynamics. The results revealed that ERDRP-0519 reduced viral entry and enhanced clearance while GHP-88309 improved target cell growth and increased the rate of infected cell death. These findings suggest that both drugs are potentially effective measles treatment options, with ERDRP-0519 having a direct antiviral effect and GHP-88309 aiding in immune recovery. Overall, these insights provide a foundation for optimizing treatment strategies and highlight the potential for both drugs to combat measles and related morbillivirus infections, especially in areas with limited resources and vaccines.

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.

Mathematical modeling of viral kinetics can be used to gain further insight into the viral replication cycle and virus-host interactions. However, many virus dynamics models do not incorporate the cell-to-cell heterogeneity of virus yield or the time-dependent factor of virus production. A recent study of the kinetics of the vesicular stomatitis virus (VSV) in single BHK cells determined that both the virus production rate and the yield of virus particles vary widely between individual cells of the same cell population. We used the results of this study to determine the distribution that best describes the time course of viral production within single cells. The best distribution was then used to incorporate time-varying production into a standard model of viral kinetics. The best-fit model was determined by fitting potential distributions to cumulative viral production from single cells and comparing the Akaike Information Criterion (AIC). The results show that the best fit for most cells was log-normal. Time-dependent viral production was modeled with an integro-differential equation that incorporated the log-normal probability distribution into a standard constant production model of viral kinetics. This time-dependent model was compared to one of constant production by examining the differences between the viral peak, time of the peak, upslope, downslope, and area under the curve. These findings could have further-reaching implications for helping define the time course and nature of a particular virus infection within the human body as well as improving the dose-timing and efficacy of anti-viral treatments.

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.