Strong gravitational lensing provides a natural magnifying effect for the study of the most distant galaxies. While there have been studies on the physical properties of star-forming clumps in strongly lensed galaxies, there is a critical need to automate the process of identifying these clusters, especially in scenarios where high flux density regions are to be discovered in large imaging surveys. Typical methods of clump identification rely on contrast enhancement through image smoothing and subtraction, followed by the use of visual and automatic source detection software. While generally effective, these approaches require careful parameter tuning and manual validation, limiting their efficiency and reproducibility. We present a novel software pipeline titled SUMAC (Software for Uniform Manifold Approximation of Clusters) that automatically processes FITS files of lensed galaxies, reduces the data using Uniform Manifold Approximation and Projection (UMAP), and outputs a topological map clustering together pixels with similar characteristics. Users can specify parameters of interest, including flux, spectral energy distribution, and morphology. We utilize JWST/NIRCam imagery of the z =2.481 lensed galaxy SGAS1110, confirming the functionality of SUMAC by automatically tagging points in the UMAP topological space, mapping them back to the imagery of the lensed galaxy to show alignment with visual star forming clusters. We additionally analyze spectroscopic data for the galaxy, ensuring pixels that SUMAC identifies as corresponding to star-forming clumps match characteristics such as age, metallicity, and emission line ratios that are indicative of star formation. SUMAC’s ability to handle large datasets efficiently, without requiring manual validation or extensive parameter tuning, ensures a more reproducible and scalable approach to high-redshift galactic analysis. SUMAC has the potential to be a valuable tool in the field of astronomical image processing, increasing the efficiency and accuracy of galactic dynamics studies.

Graphene, a single layer of carbon atoms, is a naturally abundant Dirac semimetal that is turning heads for its interesting electrical properties and tunable phase transitions at nano-scales. Prior research shows novel phases of matter arising when a bilayer sheet of graphene is stacked atop a trilayer sheet of graphene at some small relative angle. This particular geometric configuration gives rise to flat electronic bands near the Fermi level where, at low temperatures, electron-electron interactions dominate the physics of the system. Correlated topological states at integer and fractional filling of these electronic bands have previously been observed in this material, but how these states evolve with twist angle is not well understood. We present our ongoing analysis of Bernal bilayer-trilayer graphene at varying twist angles (0.8-1.7 degrees) to uncover how the geometry of our material changes these correlation-driven states. This work contributes to our rapidly evolving understanding of electron behavior in two-dimensional materials, which has future implications in quantum computing and other electronics innovations.   

Pseudomonas aeruginosa, a rod-shaped, Gram-negative bacteria, can cause various opportunistic infections, and it is a common pathogen in hospitals because of its antibiotic resistance and virulence. In P. aeruginosa, virulence is primarily regulated by cyclic adenosine monophosphate(cAMP), which binds to two effector proteins: virulence factor regulator(Vfr) and cAMP-binding protein A(CbpA). As cAMP binds to Vfr, this secondary signal promotes transcription of genes involved in virulence, such as the type IV pili system, which mediates twitching motility, and the Type III secretion system, which releases toxins into the host cell cytoplasm. However, regarding CbpA, all that is known so far is that its expression is strongly regulated by cAMP-Vfr signaling, and cAMP-CbpA binding localizes this protein to the P.aeruginosa cell pole. My project aims to determine the function of CbpA and how this effector protein regulates the cAMP-related processes of P.aeruginosa. To meet these goals, I have generated a construct that overproduces CbpA and am making mutant strains lacking cbpA. Using these constructs, I will evaluate how CbpA influences cAMP levels using a fluorescence reporter and assess its function in twitching and swimming motility using macroscopic assays.  Given that cbpA is regulated by cAMP-Vfr signaling, I will perform these experiments in strains of the wild-type (normal cAMP levels), ∆cyaAB(lacking cAMP synthesis, low cAMP levels), and ctx::araBAD-cyaB(inducible cAMP synthesis, high cAMP levels).  These experiments will provide insights into the roles of CbpA in P.aeruginosa virulence and motility. A deeper understanding of cAMP signaling and its effectors will enhance our understanding of the pathogenesis of P. aeruginosa, facilitating the development of therapeutic strategies against its infections.

In Escherichia coli, the Cpx system is understood to be a two-component cell envelope stress response system. In Pseudomonas aeruginosa however, the Cpx system is largely unstudied. Based on predictive modeling, the Cpx two-component system in P. aeruginosa is thought to involve interactions with two novel accessory proteins, PA3203 and PA3207. Previous genetic analysis in our lab has indicated that PA3207 acts as a negative regulator of Cpx signaling, while PA3203 promotes activity of the system. I evaluated biochemical interactions between these two proteins using the Bacterial Two-Hybrid assay. I generated N- and C-terminal fusions to two functional domains (T18 and T25) of an adenylate cyclase enzymatic reporter. Adenylate cyclase activity, occurring when T18 and T25 were brought into proximity by fusion protein interactions, was measured by a qualitative color assay on MacConkey agar. By this method, I confirmed functional interactions between PA3207 and cytoplasmic signaling domains of both CpxS and CpxR. Interactions between PA3203 and CpxSR were also detected, but were more dependent on the orientation of protein fusions. These findings indicate that CpxSR signaling is regulated through protein-protein interactions with multiple accessory proteins, a unique mechanism among bacterial two-component systems.

Dehydration is a silent but pervasive health risk, particularly for older adults in assisted living home settings, where prevalence rates can reach up to 60%. Medications that increase fluid loss place seniors at a heightened risk, leading to severe complications including urinary tract infections, falls, cognitive decline and hospitalisations. Caregivers continue to struggle to monitor fluid intake effectively, with less than 10% maintaining consistent hydration logs. Existing hydration monitoring solutions are often invasive, expensive and poorly suited for non-medical care settings. To address this critical issue, we developed a novel, non-invasive hydration monitoring system designed for elderly care environments. Unlike existing methods that rely on highly variable sweat salt concentrations, our approach leverages ultrasound-based elasticity measurements to assess hydration status. Changes in hydration levels alter the biomechanical properties of skin and muscle, affecting the speed at which ultrasound waves travel through tissue. By using a dual-transducer system to induce and measure shear wave propagation, we can quantify hydration status in real-time. The device provides both quantitative readouts for longitudinal tracking and intuitive qualitative feedback, similar to a blood pressure monitor's high-normal-low classification, ensuring ease of use without specialised training. Initial testing demonstrates promising accuracy and usability, positioning our solution as a practical solution to improve hydration management, prevent dehydration-related complications, and enhance quality of life for elderly residents. By empowering caregivers with a reliable, accessible hydration monitoring tool, our solution has the potential to significantly reduce healthcare costs, improve patient outcomes, and transform hydration care in aging populations. 

2D van der Waals materials are composed of atomic layers held together by weak van der Waals forces, which allows them to be separated into individual 2D sheets that are only a few atoms thick and exist in a single plane. When 2D layers are stacked together the resulting heterostructure often exhibits interesting electrical, optical, thermal, and mechanical properties. The most well-known van der Waals material is graphene, which is often layered with hexagonal boron nitrate (hBN). Peptides are short chains of amino acids, which form the building blocks of proteins. They are crucial in various biological processes, such as cell growth and development. Peptide-based materials hold great promise in fields such as drug delivery and nanotechnology due to their ability to self-assemble and interact with other molecular structures. In this research, we aim to incorporate peptides into graphene-hBN heterostructures to study the interaction between these two material systems. We focused on using dry transfer techniques to pick up peptide sheets with graphene and hBN. Through careful documentation of pick-up attempts, we can refine our approach and optimize the conditions for effective peptide incorporation. These results provide insight into the challenges in integrating biological components into van der Waals heterostructures and will inform future applications of these hybrid structures. Understanding how peptides can be effectively integrated into layered systems is crucial for advancing functional biomaterials. By refining peptide pickup and incorporation techniques, this work contributes to the broader goal of designing tunable, bio-inspired materials with potential applications in medicine and advanced manufacturing.

Clathrin mediated endocytosis (CME) is a cellular process that is critical for internalizing nutrients, molecules, and involved in drug delivery and viral infection. During CME, individual actin proteins assemble into filaments that produce force to help internalize clathrin coated pits against membrane tension. It has previously been shown that in vivo actin networks assemble non-uniformly around an endocytic vesicle. However, there is little understanding of how the cell leverages this non-uniformity and the variables that influence the degree of non-uniformity. Due to the small scale of the molecules involved in endocytosis, we used a stochastic, agent-based simulation to test what conditions impact actin network formation at a high resolution. We studied how varying the distribution of the actin branch nucleator Arp2/3 complex affects CME progression. We hypothesized that non-uniform localization of the Arp2/3 complex around sites of CME would drive the formation of a non-uniform actin network. To test this idea, we analyzed data from simulations with varied distributions of Arp2/3 around the endocytic vesicle (n=50 runs for each condition). We utilized the Wasserstein Distance between distributions as a quantitative metric of the non-uniformity in actin networks, studied the change in uniformity over time, and correlated this property with internalization amount. We found that median internalization was robust to varying the distribution of Arp2/3, but that with smaller regions of Arp2/3, non-uniform networks were able to internalize more. While our findings provide a deeper understanding of the conditions under which non-uniform networks assemble in CME, they also prompt further exploration of the underlying mechanisms of non-uniform networks.

During neonatal inter-facility transport there is a critical need to accurately measure heart rate. The electrocardiogram (ECG)  signals are particularly noisy during transport due to factors such as road noise and infant movement. This inaccuracy leads to false alarms from patient monitors when the measured heart rate values fall out of range. The Pan-Tompkins algorithm is commonly used to measure heart rate from ECG signals but frequently fails under these conditions. This project introduces a novel variation of the Pan-Tompkins algorithm, using the derivative of the ECG signal with additional filters specifically designed to target transport-related noise in neonatal ECGs. We test this modified Pan-Tompkins against the traditional Pan-Tompkins on neonatal transport data to determine if it is more effective for neonatal transport. Each algorithm is applied to a common set of ECG signal patterns taken from a real neonatal transport. The different patterns are classified as clean, somewhat noisy, or very noisy. Each algorithm will be evaluated on Sensitivity and Positive Predictability for each pattern. This research will help save the lives of neonates by reducing false alarms, which will in turn reduce alarm fatigue for providers and draw their attention only when it is truly necessary.

Pediatric Autoimmune Neuropsychiatric Disorders Associated with Streptococcal Infections (PANDAS) occurs when a streptococcal infection triggers an abnormal immune response, leading to neuroinflammation in the basal ganglia, causing sudden-onset OCD and other neuropsychiatric symptoms. Current treatments include antibiotics, cognitive-behavioral therapy, selective serotonin reuptake inhibitors, and anti-inflammatory medications (NSAIDs, corticosteroids). While antibiotics target infection, they often fail to resolve persistent immune dysfunction. Some patients experience recurring symptoms, suggesting an autoimmune-driven mechanism beyond direct infection. Despite growing research, PANDAS remains controversial. Some clinicians support an autoimmune model, linking streptococcal infections to neuropsychiatric symptoms; others argue that evidence is inconclusive or that PANDAS is not a distinct disorder. Skeptics cite inconsistent diagnostic criteria, patient variability, and limited large-scale clinical trials. Additionally, the lack of a clear biomarker and symptom overlap with other childhood-onset OCD and tic disorders create diagnostic uncertainty. Intravenous Immunoglobulin (IVIG) has shown promise in modulating immune responses, reducing autoantibody activity, and lowering neuroinflammation, offering a complementary therapy. However, placebo-controlled trials remain limited, and the synergy between IVIG and antibiotics remains underexplored. This literature review seeks to fill that gap, evaluating the combined efficacy of IVIG and antibiotics in treating PANDAS-associated OCD. It examines whether dual therapy leads to better clinical outcomes than monotherapy and identifies which antibiotics work best with IVIG. Drawing from existing studies on similar conditions and neuroinflammatory mechanisms, this research synthesizes clinical trials, case studies, and immune-response data to explore the therapeutic synergy of these treatments. Preliminary evidence suggests IVIG and antibiotics together may better address both infectious and immune components, potentially improving outcomes. However, further research is needed to optimize treatment protocols, refine diagnostic criteria, and expand knowledge on immune-brain interactions in pediatric neuropsychiatric disorders. Future implications include refining diagnostic criteria, identifying biomarkers, and expanding research on the immune-brain connection in pediatric neuropsychiatric disorders.