Candida albicans (C. albicans) a gut commensal fungus can form filaments and become harmful under certain conditions. Low gravity has been reported to increase microbial virulence gene expression and enhance C. albicans resistance to amphotericin B. Here, we investigated whether simulated low gravity affects C. albicans sensitivity to caspofungin and alters expression of the hyphal-associated genes HWP1 and ALS3.

SC5314 C. albicans strains were grown on Mueller-Hinton and YEPD agar plates. Simulated low gravity was generated using a clinostat. Caspofungin sensitivity was assessed using the Kirby-Bauer assay. Gene-specific primers and polymerase chain reaction (PCR) were used to evaluate HWP1 and ALS3 expression.

After 5–6 days, low gravity had no effect on caspofungin sensitivity in yeast grown on Mueller-Hinton plates. However, prolonged exposure significantly reduced the zone of inhibition (ZOI) from 273±32 mm² in controls to 174±20 mm² under low gravity at 12 days (P<0.05), and from 248±30 mm² to 110±26 mm² at 13 days (P<0.001). On YEPD plates, 5–6 days of low gravity exposure also produced no significant change. In contrast, low gravity significantly increased the ZOI at 12 days, from 95±31 mm² in controls to 191±13 mm² (P<0.01). No significant differences were detected in HWP1 or ALS3 expression at any time point.

These findings indicate that simulated low gravity influences Caspofungin sensitivity in a time-dependent manner and the Caspofungin sensitivity varies with growth medium. Further studies are needed to determine the mechanisms underlying these effects during adaptation to altered gravity.

Previous research shows that supraphysiologic estrogen levels induce C. albicans morphology shift from yeast to invasive filamentous form. In this study, we investigated whether the level of estrogen found in critically ill patients can modulate C. albicans morphology. We measured C. albicans filament length in the presence or absence of 1nM estrogen in two  different yeast liquid media. However, the presence of estrogen made no substantial change in filament length compared (18.24±0.58 µm) to our positive control fetal bovine serum (61.27±1.11 µm). Therefore, in order to simulate the environment of the gut, C. albicans filament growth in the presence or absence of 1 nM estrogen was tested in presence of three mammalian epithelial cell lines (T84, Caco2 and MDCK). Only in the presence of MDCK cells with estrogen, filament length was longer (45.33±0.91 µm)  compared to HPBSS alone with estrogen (36.65±0.55 µm, P<0.001)  in the absence of cells. Conversely, the presence of T84 cells alone significantly decreased filament length (28.30±3.52 µm) compared to culture media (HPBSS) alone (40.23±0.77, P<0.001). In a simple phosphate buffered solution (PBS), here the presence of cells caused a significant increase in filament length (13.53±0.36 µm) compared to the absence of cells, regardless of cell type (0.00±0.00 P<0.001). In PBS, estrogen decreased filament length (12.14±0.43 µm) only in presence of T84 cells compared to T84 no estrogen (14.52±0.39 µm, P<0.001). Thus we conclude that estrogen at 1 nM has limited effect on filament length in our conditions.

This project builds upon the Clark research team’s goal of understanding how the transcription factor CooA (carbon monoxide oxidation activator) activates its DNA-binding function upon changes at its heme domain (i.e., an iron porphyrin complex) when bound to carbon monoxide (CO). This research has broader implications, as analogous gas-sensing proteins are potential drug targets. Previous work showed that replacing heme with a different metalloporphyrin activated DNA-binding even without carbon monoxide. However, it is poorly understood how these changes at the heme domain activate DNA-binding, which takes place remotely. This study will investigate how the heme group affects CooA’s structure by employing chemical denaturation to elucidate differences in thermodynamic stability with various metalloporphyrins and using circular dichroism to characterize changes in the protein’s secondary structure.

Zeolites are microporous crystalline minerals synthesized using silicon, aluminum and oxygen. They feature a 3D honeycomb-like framework with channels and cavities that trap, filtrate or separate molecules and exchange ions. Because of the zeolite’s ability to absorb different types of molecules, this project chose the molecule known as Brooker’s merocyanine dye because of its strong zwitterionic character, environmental sensitivity, and structural alignment properties  in order to observe and compare the effects of different properties on absorption. The polarity of the solvent affects the zwitterionic character of the dye which could change the absorption behavior. Samples of the mordenite zeolite were stirred and refluxed with a diluted dye solution composed of Brooker’s merocyanine, hydrochloric acid and either water or 2-propanol as the solvent. Samples of the solution after reflux were then compared to a reference of the original dye solution using UV-visible spectroscopy to calculate the molecules of dye absorbed per gram of zeolite. The refluxed mordenite was filtered and dried for BET analysis to determine whether the dye filled the channels of the zeolite or sat on the surface of the crystals. The UV-Vis calculations suggested that the mordenite absorbed an average of 2.8E+20 molecules of dye per gram of zeolite in water and 5.8E+19 in propanol, so the dye was absorbed more efficiently using water. These results help to build a model of ion exchange in zeolites across different conditions and increase understanding applicable to other ion-zeolite interactions.

Healthcare organizations increasingly integrate artificial intelligence and machine learning into database management systems to improve accuracy, productivity, and patient outcomes. When training data is biased or inaccurate, these models may misanalyze, misinterpret, or mispredict clinical data, with potential consequences for minority patients. This conceptual scoping review examines how algorithmic bias in healthcare database systems is reported to affect racial and social minority groups and relates to inequity in healthcare outcomes (i.e. diagnosis, treatments) and proposes a framework that maps the relationships between algorithmic racial biases, their effects on patient outcomes, and corresponding detection methods. 

The research identifies recurring sources of algorithmic racial bias in peer-reviewed literature. Two of these are presented here: representation gaps in training data and measurement and labeling errors in healthcare databases. These patterns manifest in the underdiagnosis and/or undertreatment of Black, female, Hispanic, Asian, and other patient minorities. 

The framework links these recurring sources to detection methods grounded in analytical and database management practices. Representation gaps may be detected through proxy variable screening (e.g. ZIP code, country of origin) to identify features that encode minority group membership, and through chi-square goodness-of-fit tests that compare sample demographics with the served population. Measurement and labeling errors may be detected through label validity review and cross-verification of outcome definitions across clinical sites. 

GoBabyGo is a network of chapters that build modified ride-on toy cars that give young children with disabilities independent mobility (Huang & Galloway, 2012). Self-initiated movement during early childhood supports cognitive, social, and motor development. 

GoBabyGo Valpo is a university chapter that has built 14 modified ride-on cars for children with disabilities, at no cost to their families. Occupational therapy and engineering students work together on each car, and children are referred by local pediatric therapy clinics. 

Family-centered practice is an established framework in pediatric care: each family decides its own level of involvement in decision-making, and parents hold ultimate responsibility for their child’s care (Rosenbaum et al., 1998). 

Engineering students and faculty then reviewed each stage of the design process—child evaluation, car build, and car delivery (Grab Your Keys Day)—and revised the engineering design documents used at each stage. 

In Spring 2026 (post family-centered practice training), revised documents were developed and tested for the spring design cycle. Revisions have continued through Summer 2026, as students identified sections that were missing, unclear, or incompletely communicated between OT and engineering. 

Not enough time has elapsed to measure whether family-centered practice affects child car use. But we can report substantial changes in design documentation, and other design teams can adopt these changes as well.

Traditional clinical practice training relies on lectures and shadowing to understand complex procedures. While these methods are often sufficient for many diagnoses or simple procedures, complicated techniques require further training for sufficient patient outcomes. This training is often best done with cadavers; however, due to the cost and complexity of training with cadavers, surgical phantoms are often used as a substitute. For many rare and complex conditions, these resources are either unavailable or too expensive. Additive manufacturing offers powerful capabilities for creating tools to support this form of clinical education. One application that greatly benefits is cardiac cases involving coronary anomalies. These cases can be segmented from clinical data and 3D printed to provide greater spatial understanding than photos or other educational methods. Phantoms can be cast from 3D-printed molds for uncommon cases that might not be commercially available. Endoscopic practice for rhinology was also examined using a 3D-printed trainer. These applications were developed over a single summer, demonstrating the rapid development and iteration possible. Future work will examine these models to quantify the benefits of additive manufacturing in these applications.        

Law enforcement agencies collect substantial amounts of crime data, yet traditional methods of organizing and interpreting this information can reinforce outdated assumptions about criminal activity. This research, conducted in partnership with the Western Springs Police Department in Illinois, explores how Geographic Information Systems (GIS) can improve the accessibility, interpretation, and communication of crime data to support evidence-based policing.

Using theft and burglary reports from May 2025 to May 2026, the project sought to examine existing perceptions of criminal activity and determine whether those assumptions aligned with documented incidents. Through GIS mapping and spatial analysis, individual police reports were transformed into accessible visual representations of crime patterns throughout the community. These maps provided a clearer understanding of where incidents occurred and allowed department personnel to examine geographic distributions rather than relying solely on historical perceptions or individual experiences.

The research emphasized the importance of questioning established assumptions through geographic evidence while developing more efficient methods for accessing and communicating departmental information. Rather than focusing exclusively on predicting future crime, the project demonstrated how spatial visualization can make existing records more useful for everyday law enforcement operations.

Ultimately, this research illustrates how GIS can serve as a practical decision support and communication tool for smaller police departments. By making crime data more accessible, understandable, and geographically meaningful, law enforcement agencies can strengthen internal communication, reevaluate longstanding assumptions, and make more informed decisions about public safety.

Large amounts of quality control data are collected throughout various significant stages of industrial manufacturing, yet much of it is recorded but underutilized. During a two-stage Co-Op in the Quality Management Department at McWane Ductile Ohio, one of the nation’s top producers of ductile iron for water transportation and utility pole construction, data analysis and modeling was performed on critical production and testing data primarily in Python via Google Colab. This data was generated from a critical quality inspection point via a laser thickness gauge and looked to address a common failure point that threatened the viability of the product. While the non-optimized analyses were moderately useful to the company, the visualizations created to communicate said analysis were made without adherence to data visualization principles and struggled to communicate the information. A selection of the original projects was evaluated against Edward Tufte’s ideas as well as Gestalt principles, and areas that benefit from interactivity were identified. Several visuals were redesigned, with feedback and responses from a wide range of parties discussed as well. Generally, the comparisons demonstrated that minor changes can substantially improve the clarity of a finished product, provided that they improve communication of the data to the invested audience. Presented are the original projects, evaluation, and redesigns, along with implications for students preparing for internships involving any data presentation.

One of the most frequently cited economic studies of the past fifty years has been David Card and Alan Krueger’s “Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania”, which presented key findings that raising the minimum wage had on employment. I plan to perform a comprehensive and full replication of the study in conjunction with an exploration of some of the criticisms of the statistical methodology that was used, making use of key concepts I’ve been learning in my classes. Furthermore, this project seeks to gain a better understanding of what is the most commonly cited study on the minimum wage, given how prevalent this study is in political discourse.

Planetary nebulae (PNe) contain either carbon-based or oxygen-based dust or a combination of the two, though the exact molecular composition remains unknown. Here we analyze oxygen-rich PNe, whose dust is suspected to include silicate (SiO2)n clusters. We use methods of computational quantum mechanics to determine the equilibrium structures of (SiO2)n clusters for n=12−24 and analyze their stability and structural features. We then calculate the binding energy and the infrared (IR) spectra of the most stable silicate structures for each value of n. By comparing these spectra to observed spectra of oxygen-rich PNe, we hope to determine the molecular composition of the dust. This knowledge will improve our understanding of PNe formation and stellar evolution.

One goal of the Solenoidal Tracker at RHIC (STAR) experiment is to understand the gluon contribution to the overall proton spin of ½ ħ. Longitudinally polarized proton beams are collided at the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory. The asymmetry (A_LL) in neutral pion (π0) production from these collisions is sensitive to the gluon spin contribution. The π0s promptly decay into two photons whose energies and positions are measured by the Endcap Electromagnetic Calorimeter (EEMC). Multiple quality assurance (QA) checks are performed to ensure that the data coming from the EEMC is robust for precision ALL measurements. After QA, reconstructed invariant mass distributions are fitted using various background models to extract the π0 yield and calculate A_LL. Variations in the extracted yield due to different background functions allow for the estimation of the systematic uncertainty associated with background modeling. The status of this analysis on the 2013 (√s = 510 GeV) datasets will be presented. 

The development of low-cost, highly active, and durable electrocatalysts for the oxygen evolution reaction (OER) remains a challenge for electrochemical energy conversion. Dynamically stabilized active sites on high entropy transition-metal hydr(oxy)oxide surfaces represent a new class of OER catalysts. By incorporating different first-row transition metals into layered hydr(oxy)oxide frameworks, we evaluate distribution of local electronic environments that can optimize adsorption energetics. We have calculated Fe(OH)3 binding energies on different hydr(oxy)oxides, which is proposed as a descriptor for OER activity. Second-neighbor ion substitutions are studied for their impact on the binding energies of Fe complexes on the hydr(oxy)oxides. Additionally, binding energies of the Fe complexes depends on the choice of spin configuration of the system.

Nuclear Physics students and faculty at Valparaiso University worked on three experiments: the STAR experiment, the ePIC experiment, and the nEDM experiment. One of STAR’s goals is understanding the gluon’s contribution to the proton’s overall spin of ½ ħ. At the STAR experiment, polarized proton collisions, provided by the Relativistic Heavy Ion Collider (RHIC), produce numerous neutral pions (𝜋0) that promptly decay into two photons. The photon energies are measured by the Endcap Electromagnetic Calorimeter (EEMC) and used to reconstruct the 𝜋0 invariant mass. Our work supports 𝜋0 spin asymmetry analysis by investigating systematic uncertainties through alternate background modeling of 2013 data and Quality Assurance (QA) on the 2015 data set. Ahead of BNL’s transition from RHIC to EIC (Electron-Ion Collider), the EIC’s first detector, ePIC, had six hadronic calorimeter modules tested at a CERN test beam in May. Using this data, we have been performing HGCROC waveform analysis and analyzing the effects of changing preamplifier settings. The neutron Electric Dipole (nEDM) experiment at Los Alamos National Laboratory is designed to search for the nEDM at the level of 10-27 e*cm. The precession frequency of neutrons in a weak magnetic field and a strong electric field are extremely sensitive to even the smallest stray magnetic fields, especially very tiny magnetic dipoles in the detector components. A process involving precise magnetic scanning, sonic cleaning, and magnetic characterization of the parts going into the MSR will be presented.