Date: March 26th, 2025

Time: 10 AM - 2 PM

Venue: Rowan University, Chamberlain Student Center

8 am: Check-in for Interactive Displays / Poster Displays open - First Floor Hallway

9:45 am: Welcome Program - The Pit

• All posters should be ready by 9:45 am

  • Room 144 (Posters 1-41)

  • Room 221 (Posters 42-75)

  • Atrium - new SC expansion (Posters 76-98)

10 am - 2 pm: Graduate Students and Post-Doctoral Fellow Poster Displays Open - Hallways, Room 144, and the New Building Lobby

• Posters should not be taken down until 2 pm (if you cannot stay

11:30 am: Lunch - Room 153 - Grab-n-Go; Seating available in all areas of the Student Center (not in Rm 153)

2:00 pm - People's Choice Awardees votes are turned in  (hand in your votes -- which are tiny owl thimbles given to you as a "vote") to be considered for the people's choice award of $50. 

3:30 pm - 4:15 pm: Award Presentations - Atrium Stage

• Research Awards

• Poster Awards

4:30 pm: Graduate Students Reception - Owls Nest

First Name     Last Name College/School

Rachel         Carney         Ric Edelman College of Communication and Creative Arts

Christina Newlands              College of Education

Shaheer          Chaudhary            College of Science and Mathematics

Anand Kumar Upparapally     College of Education

Anu Deevi         Rowan-Virtua School of Osteopathic Medicine

Prithvi Ravi Henry M. Rowan College of Engineering

Evans Omondi College of Science and Mathematics

Find poster numbers sorted by last name:

Poster #          Last name                      First name

99 Acquah Christopher

34                   Al Issa                                Moayad

33                   Alapatt                               Catherine 

35                   Alfaris                                 Ruqaya

36                   Alfaris                                 Ruqaya

5                     Ali                                      Izhar

37                   Ali                                      Abdelrahman

8                     Antisell                               Morgan 

97                   Argueta Donohue                Jose de Jesus

38                   Asad                                  Yusuf

39a                 Baditha                              Anil Kumar

39b                 Baditha                              Anil Kumar 

41                   Bain                                   Ian

42                   Basukala                            Kebisha

3                     Begum                               Mosa Asia 

4                     Begum                               Mosa Asia

6                     Boltz                                  Lillian

1                     Bonino                               Amanda

7                     Bortey                              Charlotte

43                   Boyle                                 Brett

90                   Bozarth                              Samantha

9                     Burrell                                Brandon

44                   Butler-Morton                      Brittany

45                   Cantor                                Ethan

46                   Chaudhary                         Mohit

88                   Corbett                               Claire

10                   De Salas                            Lilliana

93                   DeBellis                              Korie

71                   Edalatian Zakeri                  Shahab

11                   Elias                                   Elias

47                   Faysal                                Atik

12                   Gabriel                               Julia

48                   Gali                                    Lakshmana Ravi Raj

94                   Ganji                                  Vignan

72                   Gantumur                           Narangerel

49                   Gao                                   Barnabas

73                   Guner                                 Liza

86                   Hansen                              Emily

50                   Hassinger                           Dominique

51                   Hazaveh                             Zaynab

52                   Heras                                 Matthew

53                   Islam                                  Md Sadman

13                   Kaasaragadda                    Yagna

54                   Keblawi                              Mohamad

55                   Khelifi                                 Amine

56                   Khelifi                                 Amine

91                   Knapp                                Christopher

78                   Kopchick                            Emily

92                   Kulkarni                              Rashmi

14                   KUMAR                              ADARSH

57                   Maaz                                  Muhammad

15                   Mabtoul                              Samira

58                   Malino                                Heather

59                   MALLURU                          SWATHI

87                   Marano                              Nicholas

79                   Martino                               Katelyn

16                   Mazahreh                           Janine

77                   McGraw                             Jennifer

17                   Moore                                Rosalind

60                   Nadi                                   Elias

95                   Nalla                                  Shreya

96                   Ngo                                    Megan

18                   Nitchie                                Frederick

61                   Pagliocca                           Nicholas

62                   Paolello                              Mitchell

80                   Papadopoulos                     Eleni

19                   Paradis                              Nicholas

20                   Paul                                   Krishna

63                   Paupst                               Tyler

81                   Pizutelli                              Vanessa

31                   Popova                              Liya

64                   Prahaladan                         Varsha

82                   Predale                              Haven

74                   Recktenwald                       Matthias

83                   Rolling                                Christal

65                   Rostami                              Mohammad

66                   Saidi                                  Ahmed

30                   Sammir                              Md Redwan

21                   Sare                                   Hadarou

23                   Sharma                              Manobin

67                   Siddique                             Abu Bakar Md

68                   Singh                                 Amit

84                   Sloand                               Timothy

98                   Tellez Jimenez                    Olivia

89                   Tkaczynski                         John

22                   Towolawi                            Bamidele

2                     Truong                               Tayliyah 

24                   Tumpa                               Mst Afroza Alam

69                   Varma                                Vaibhavsingh

70                   Varma                                Vaibhavsingh

85                   Wannen                             Erin

25                   Webber                              Nakoa

26                   White                                 Abigail

27                   Williams                             Dawn

75                   Yang                                  Joshua

32                   Young                                Victoria

76                   Young                                Rachel

40                   Yu                                      Hoi Yan

28                   Zangaro                             Jacob

29                   Zhang                                Ariel

1 Amanda Bonino

MA School Psychology

Advisor(s): Dr. Roberta Dihoff

Title: Rowan University Autism PATH  Mindfulness Benefits Goal Orientation of Neurodiverse Students

Abstract: This study explores the benefits of mindfulness practices on the goal orientation and anxiety level of Neurodiverse Students within the Rowan University PATH Program. Research indicates that practices such as Mindfulness & Meditation enhance self-awareness and emotional regulation. Through a hands-on approach with a trained PATH Mentor, students will explore the wellness aspects of Affirmation Statements, Meditation and Creative Outlets for Creating Goal Statements.

2 Tayliyah Truong

MS Emergency & Threat Management

Collaborator(s): Smith, Riyon

Advisor(s): Desmond Miller

Title: Strengthening Disaster Resilience: Public-Private Partnerships in Emergency Management

Abstract: Public-private partnerships (PPPs) play a crucial role in emergency management, bridging gaps between government agencies and private sector resources. However, past emergency response programs have struggled due to reliance on volunteerism without sustainable incentives. This proposal introduces the Emergency Management Reserve Corps (EMRC), a structured and incentivized workforce designed to integrate private businesses, unions, and government agencies into disaster response. Unlike traditional volunteer-based models, the EMRC sustains engagement through financial incentives and workforce development opportunities, ensuring a resilient and rapid disaster response. The program will provide structured training, tax benefits, and career pathways, addressing key gaps in New Jersey’s emergency preparedness and setting the stage for a scalable national model.

3 Mosa Asia  Begum

PhD in Complex Biological System

Collaborator(s): Begum, Mosa Asia; Brock, Michelle C; Heindl, Jason

Advisor(s): Heindl, Jason

Title: Investigating the Role of FeuP (Atu0970) and FeuQ (Atu0971) in Agrobacterium tumefaciens Biofilm Formation and Motility

Abstract: Agrobacterium tumefaciens is a soil-borne, Gram-negative bacterium responsible for plant crown gall disease, producing significant economic losses in agriculture by disrupting nutrient flow and weakening plants. Biofilm formation and motility are critical factors in its pathogenicity and environmental adaptation. The two-component regulatory systems FeuP (Atu0970) and FeuQ (Atu0971) is hypothesized to play a central role in these processes. In this study, we investigated their contribution to A. tumefaciens biofilm formation and motility using single- and double-deletion mutants. 

We analyzed wild-type, single mutant (∆atu0970, ∆atu0971), and double-mutant (∆atu0970 ∆atu0971) strains through a swim motility assay by measuring the swim ring diameter over seven days, while biofilm formation was quantified using a static coverslip assay and binding of crystal violet by adherent biomass. Our findings show that FeuP and FeuQ are essential for optimal biofilm formation in A. tumefaciens, with their combined deletion severely impairing this process. However, these mutations do not significantly affect swim motility under the tested conditions. The growth defects observed in the swim motility of the double-deletion mutant suggest a broader regulatory role for FeuP and FeuQ. 

These results provide valuable insights into A. tumefaciens' survival strategies and adaptation to different environments. Future studies are required to understand how this regulatory system influences bacterial biology and host interactions, potentially offering new strategies for controlling biofilm formation and improving agricultural biotechnology.

4 Mosa Asia Begum

PhD in Complex Biological System

Collaborator(s):  Begum, Mosa Asia; Jones, Elizabeth Grace; Urban, Matthew ; Zangaro, Jacob T. ; Webber ,Nakoa ; Nucci, Nathaniel V.

Advisor(s): Nathaniel V. Nucci

Title: Investigating the Structural Implications of Lysine Acetylation in Histone-Like Proteins (HU) from Bacillus subtilis: Potential Implications for Biofilm Stability and Drug Resistance

Abstract: Histone-like proteins (HU), small dimeric DNA-binding proteins, play a crucial role in bacterial chromatin organization, via the canonical DNA binding site, and biofilm stability, via the non-canonical binding site. Biofilm stability is a key factor contributing to antibiotic resistance in many bacteria. Lysine residues K41 and K86 in the non-canonical binding site of HU Protein are essential for DNA binding and nucleoid compaction. Acetylation of these lysine residues has been shown to significantly impact DNA binding by reducing affinity. Acetylation of K41 was shown to decrease DNA binding affinity, leading to nucleoid relaxation. However, acetylation of K86 weakens DNA interaction, promoting chromosome de-condensation.

In this study, we tried to investigate the impact of lysine acetylation mimic mutations (K41Q and K86Q) on HU’s DNA-binding properties, focusing on their potential role in biofilm formation and drug resistance mechanisms. We analyzed wild-type and mutant HU proteins that were recombinantly expressed, purified, and encapsulated in reverse micelles (RMs) for high-resolution 15N HSQC NMR spectroscopy. Structural changes were analyzed in aqueous and RM environments to evaluate how mutations influence protein structure. These findings reinforce the model that lysine acetylation serves as a regulatory mechanism for bacterial nucleoid architecture, biofilm formation, and potentially influencing bacterial drug resistance. Future studies are required to elucidate further HU’s structural changes upon DNA binding and how those changes are regulated by lysine acetylation.

5 Izhar Ali

MS in Data Science

Advisor(s): Shen-Shyang Ho

Title: SplitTracr: A Flexible Performance Evaluation Tool for Cooperative Inference and Split Computing

Abstract: SplitTracr is a performance evaluation tool used on deep neural networks (DNNs) to simplify the development overhead of split computation-based DNN models. Usage of such a tool allows the neural network to be dynamically split into component parts at any point. Our tool handles the management of configuration of hardware edge devices, export & injection of forward pass tensors during live tests, dataset handling, metrics & logging in the testing process. We examine the structure, methodology, and design choices we made to create SplitTracr, and review the results of our pre-provided base cases.

6 Lillian Boltz

PhD in Complex Biological Systems

Advisor(s): Dr. Maggie Pearce

Title: The Hunt for Phagocytic Signals Initiating Pathological Protein Aggregate Engulfment in Huntington's Disease

Abstract: A major pathological hallmark of all neurodegenerative diseases is the appearance of proteinaceous inclusions containing misfolded and aggregated proteins in selectively-vulnerable brain regions. Although the protein(s) that misfold are unique to each disease type, they all aggregate by a templated conformational conversion mechanism and are toxic when added to cells. Remarkably, abundant evidence now exists to support prion-like behaviors for protein aggregates associated with the most common neurodegenerative diseases–they have the ability to transfer between cells by seeding the misfolding of natively-folded cognate proteins. Our lab has reported that aggregates formed by mutant huntingtin (mHTT) proteins associated with Huntington’s disease (HD) transfer between synaptically-connected neurons in adult Drosophila melanogaster brains. Remarkably, we observed that aggregates generated in presynaptic axons required passage through glial cells via Draper/MEGF10-dependent phagocytosis before reaching postsynaptic dendrites. These findings suggest that while phagocytic glia are responsible for clearing neurotoxic aggregates from neurons, age- and disease-related phagolysosomal network dysfunction could lead to prion-like spreading of engulfed aggregates that evade lysosomal degradation. 

 The overall objective of this study is to further elucidate the mechanisms for prion-like aggregate spread in the brain. The approach is two-fold: (a) we will identify molecular “find me” and “eat me” signals that initiate phagocytic engulfment of mHTT aggregates from neurons, and (b) we will determine additional phagocytic and autophagy pathway components for their roles in the engulfment and clearance of mHTT aggregates. These experiments are being carried out in in vivo Drosophila models of HD and focus on genes and pathways that are well-conserved in mammals. Findings from this work will enhance our understanding of how glia respond to accumulating pathological proteins in the brain and have the potential to identify new targets for therapeutic interventions in HD and other neurodegenerative diseases.

7 Charlotte Borteley Bortey

PhD in Complex Biological Systems

Collaborator(s): Bortey, Charlotte B., Grone, Jacob ,Webber, Nakoa

Advisor(s): Nathaniel Nucci

Title: Expression, Purification and Characterization of Human dopamine D3 receptor for structural and functional studies.

Abstract: G-protein-coupled receptors (GPCRs) are the largest receptor family, regulating key physiological processes such as neurotransmission, immune response, and hormone signaling. The dopamine D3 receptor (D3R), a critical GPCR, is highly expressed in brain regions involved in motor control, cognition, and reward processing, making it a promising therapeutic target for Parkinson’s disease, schizophrenia, and other neurodegenerative disorders. However, selective drug development is challenging due to the conserved orthosteric sites among dopamine receptor subtypes and receptor dimerization. This study aims to develop a method for identifying and targeting allosteric sites for drug discovery and to measure the binding kinetics of D3R using fluorescence detection and NMR.

 We successfully expressed and purified recombinant D3R from Expi293 cells using FLAG-based purification and MNG/CHS detergent solubilization. Size-exclusion chromatography (SEC) and western blot analysis identified a monomeric ~44 kDa band and a ~100 kDa band, suggesting dimer formation. Treatment with the reducing agent DTT did not disrupt dimerization, indicating stabilization through non-covalent interactions, likely mediated by transmembrane domains (TMD I, II, IV, and V). We hypothesize that MNG/CHS detergent may contribute to dimer stability.

 In our ongoing research, we aim to employ methionine labeling for NMR to gain atomic-level insights into receptor conformation. Förster Resonance Energy Transfer (FRET) and native tryptophan fluorescence shift assays will probe ligand-induced structural changes. Investigating the effects of agonists and antagonists, such as haloperidol, on dimerization will provide insights into functional relevance. Additionally, minimal cysteine mutant development will refine dimerization mapping, while β-arrestin recruitment assays will elucidate D3R-mediated signaling. These approaches will enhance our understanding of D3R structure and function, advancing the development of selective allosteric modulators for dopamine-related disorders. 

Our findings provide a foundation for targeting D3R with high specificity, advancing precision medicine for dopamine-related pathologies.

8 Morgan Antisell

PhD in Biomedical Engineering

Advisor(s): Sophia Orbach

Title: Modeling Inter and Intra-individual Variations in Xenobiotic Metabolism

Abstract: Adverse drug reactions (ADRs) are a prevelant and costly problem to society; they are responsible for up to 10% of hospital admissions corresponding to $30 billion dollars in cost annually, as well as the failure of atleast 20% of all clinical trials. Given that many ADRs are preventable, it is vital to develop a computational framework to describe the regulation of drug metabolism on a mechanistic level and predict the expression of drug metabolizing enzymes. Six Cytochrome P450 (CYP) enzymes (CYP1A2, 2C9, 2C19, 2D6, 2E1, 3A4) are responsible for metabolizing over 90% of all clinically approved drugs. It is crucial to identify non-invasive biomarkers that can help us predict the expression of these key CYP genes. In this study, we used RNA-sequencing data from the Gene Tissue Expression project (GTEx) to obtain blood and liver gene expression data. We performed Gene Set Enrichment Analysis (GSEA) to identify potential trends in xenobiotic metabolism based on individual phenotypic factors. Correlation analyses were used to identify linear co-regulation relationships amongst xenobiotic gene families. Transcription Factor inference methods were used to characterize gene regulation with respect to expression profiles of key CYPs. Machine Learning methods, including Random Forest, Support Vector Machine, and Recursive Feature Elimination, were used to predict relative CYP expression profiles. Overall, this work seeks to describe the regulation of xenobiotic metabolism within and amongst individuals, as well as predict the expression of key drug metabolizing enzymes to enhance personalized medicine and drug safety applications.

9 Brandon Burrell

MS in Pharmaceutical Sciences

Advisor(s): Timothy Vaden

Title: Lipid bilayer permeabilities and antibiotic effects of tetramethylguanidinium and choline fatty acid ionic liquids

Abstract: Ionic liquids (ILs) have been studied as potential components in antibiotic formulations based on their abilities to permeabilize and penetrate lipid bilayer, which correlate with their antibacterial effects. Fatty acid-based ILs (FAILs), in which the anion is a long-chain fatty acid, can permeabilize lipid membranes and have been used in biomedical applications since they have low human cell cytotoxicity. In this work we investigated the abilities of several different FAILs to permeabilize lipid bilayers and how that permeabilization correlates with antibacterial activity, cell membrane permeability, and cytotoxicity. The FAILs consisted of the cations tetramethylguanidinium (TMG) or choline combined with octanoate or decanoate. These FAILs were tested on model bilayer vesicles with three different lipid compositions for membrane permeabilization using a leakage assay. They were then tested for antibiotic and membrane permeabilization on bacterial, mammalian, and yeast cells. The results show that while the octanoate-based FAILs do not form micelles and have low activities on vesicles and biological cells, the decanoate-based FAILs can permeabilize bilayers and have biological activities that correlate with the model vesicle results. The ILs with both cation and fatty-acid anion have strong activities while the decanoate alone has only minimal permeabilization and antibiotic activity. Membrane permeabilization occurs at FAIL concentrations below their CMC values which suggests that their mechanism of action may not involve micelle formation.

10 Lilliana De Salas

PhD in Complex Biological Systems

Advisor(s): Nick Whiting

Title: Green" Synthesis of Carbon Quantum Dots Using Chicken Feathers

Abstract: Carbon-based quantum dots (CQDs) are valued for their favorable optical and electronic properties while being inexpensive and biologically-friendly. While most CQDs are synthesized from the bottom-up using small-molecule precursors, different types of  agricultural wastes can also be transformed into CQDs using green chemistry. Here, we synthesized CQDs using hydrothermal solvation of chicken feathers. Samples were then purified, and the physical and chemical properties of the CQDs were characterized. Long-term, we aim to develop these carbon dots as agricultural supplements.

11 Elias Elias

PhD in Complex Biological Systems

Advisor(s): Melissa Manners

Title: Exercise promotes resilience to chronic stress and mitigates stress-induced inflammation in the hippocampus

Abstract: Besides significant benefits to physical health, exercise promotes mental health, reduces symptoms of mental illness, and enhances psychological development. However, the effects of exercise on chronic stress-induced behaviors are contradictory in preclinical studies, primarily due to the lack of data and sex-specific investigations. 

 We sought to evaluate the effects of exercise on chronic stress-induced behavioral changes in both male and female mice. Mice were subjected to an Unpredictable Chronic Mild Stress (UCMS) paradigm with accessibility to running wheels for 2 h daily. 

 Chronic stress induced voluntary wheel running (VWR) and weight loss in mice. Compared to males, increased VWR was reported in females who also regained their weight lost by the end of the UCMS protocol. Exercise promoted resilience to stress-induced hyponeophagia and increased sucrose consumption. Notably, qPCR results from our post-UCMS analysis indicated that stress induced inflammation in the hippocampi of males, accompanied by an overexpression of key proteins belonging to the Nuclear factor kappa B pathway. This sex-specific induction of inflammation was inhibited by exercise. 

Our findings imply that exercise promotes resilience to the behavioral effects of chronic stress in both sexes and mitigates stress-induced inflammation in male mice. 

12 Julia Gabriel

PhD in Pharmaceutical Chemistry

Advisor(s): Dr. Erik Hoy

Title: Comparing Enol-Keto Tautomerization Ratios using Computational Quantum Chemistry

Abstract: Tautomeric equilibria play an essential role in a wide array of natural chemical and biological reactions. Despite having structures that only differ by the position of one hydrogen atom, the chemical properties of tautomers can vary considerably. This project utilizes computational quantum chemistry software to analyze the impact of substituent effects, intermolecular interactions, and solvent interactions (implicit and explicit) on different compounds. The results utilized total free energy differences where a negative value indicates a preference of the other tautomer over the most stable one, while a positive value favors the most energetically stable tautomer. Within this presentation, two different sets of data were looked into. In the first data set, experimental values of tautomerization ratios for different compounds were generated by the experimentalists and theoretical results were compared against these values. The main goal for this first data set was to emulate and validate the experimental results by performing theoretical analysis. In the second data set, two trends were observed and analyzed by performing similar calculations from the first part. With these theoretical values validating the trends, experimental analysis will be done for future research.

13 Yagna Kaasaragadda

MS in Data Science

Advisor(s): Silvija Kokalj-Filipovic

Title: Efficient Signal Generation for Data Augmentation using AI

Abstract: Modern signal processing AI applications face increasing demands for diverse training data while operating under computational constraints. State-of-the-art generative models, though effective, often require prohibitive computational resources, limiting their practical deployment in resource-constrained environments.

We propose computationally efficient framework for synthetic signal generation utilizing a novel two-stage architecture. We combine a Vector Quantized Variational Autoencoder (VQ-VAE) with a compact decoder-only transformer to generate high-quality synthetic signals while significantly reducing model complexity and computational requirements. The VQ-VAE encodes high-dimensional signals into a discrete latent space, creating a compressed representation that enables the transformer to operate on token sequences rather than raw signals. Experimental validation on TorchSig (focusing on six prevalent digital modulation classes) and AudioMNIST datasets demonstrates that our approach generates diverse, realistic signals with substantially lower computational overhead compared to state-of-the-art generative models like Diffusion and GAN’s. The proposed methodology offers practical applications in data augmentation, model robustness enhancement, privacy preservation, RF channel estimation, and improved generalization in wireless communications and speech processing. Our contribution addresses the critical need for accessible generative modelling in signal processing applications with resource constraints.

14 ADARSH KUMAR

PhD in Pharmaceutical sciences

Advisor(s): Erik Hoy

Title: Exploring RAFT Depolymerization Mechanisms through Metadynamics Simulations and Empirical Insights

Abstract: Understanding the mechanisms of controlled depolymerization via reversible addition-fragmentation chain transfer (RAFT) is critical for advancing polymer recycling. In this study, we employ metadynamics simulations to explore the initiation and elimination pathways of RAFT depolymerization. Initiation proceeds via homolytic C-S bond cleavage, generating carbon and sulfur radicals, while simultaneous C-C bond cleavage is hindered by its high thermal stability. Elimination occurs through concerted C-S and C-H bond cleavage, resembling the Chugaev elimination, as demonstrated for trithiocarbonate (TTC), dithiobenzoate (DTB), 1-pyrrolecarbodithioate (DTP), and N-pyridine carbodithioate (PCDT). Notably, dithiooxalate (DTO) elimination directly forms carbon disulfide and ethanol, revealing unique degradation pathways for alternative RAFT end groups. Simulations quantify the energy barriers for bond cleavage, providing insights into the reactivity of RAFT end groups. TTC and DTB initiate depolymerization at 18.2 ps and 30.2 ps, respectively, with DTB’s slower initiation aligning with its lower depolymerization efficiency observed experimentally. DTO, DTP, and PCDT exhibit even slower initiation (40.8–43.1 ps), making them less suitable for depolymerization. Elimination barriers for TTC and DTB are similar (18.4–18.5 ps), but DTB’s initiation is 63% slower than its elimination, supporting its preference for elimination over depolymerization. These findings bridge theory and experiment, offering mechanistic insights into RAFT depolymerization and guiding the design of efficient polymer recycling strategies. By expanding the scope of RAFT end groups and understanding their reactivity, this work paves the way for optimizing depolymerization processes.

15 Samira Mabtoul

MS in DS

Advisor(s): Ho, Shen Shyang

Title: Uncertainty Quantification Using Graph-based Conformal Prediction for Mesh-based Simulation

Abstract: We propose an innovative methodology for quantifying uncertainty in mesh-based simulations by implementing graph-based conformal prediction techniques. This approach integrates conformal prediction algorithms with graph-theoretic representations, enabling robust statistical uncertainty quantification while preserving the intrinsic spatial and topological characteristics of mesh-based simulations. Empirical validation on a comprehensive dataset of 125 distinct fluid flow trajectories reveals an inverse relationship between predictive precision (coverage metrics) and reliability parameters (prediction intervals), with uncertainty bounds expanding proportionally as user-specified performance thresholds increase.

16 Janine Mazahreh

PhD in Pharmaceutical Chemistry

Advisor(s): Nathaniel Nucci

Title: Exploring Reverse Micelle Exchange Dynamics for the Delivery of Biologicals

Abstract: Reverse Micelles (RMs) are thermodynamically stable nanodroplets composed of a bulk organic solvent and an aqueous core stabilized by a surfactant layer. Due to the small nature of RMs, their movement is dominated by Brownian motion, causing the droplets to randomly collide, coalesce to exchange contents, and decoalesce continuously. RMs can encapsulate a wide range of molecules, making them useful for biophysical studies such as protein confinement and nanoparticle synthesis. Additionally, they hold great potential for delivering biological compounds that would otherwise degrade or fail to cross cellular membranes. Optimizing RM systems for therapeutic delivery requires a detailed understanding of intermicellar collision behaviors, as these dictate the kinetic release profiles of encapsulated molecules. The rate of exchange between RMs (kex) is primarily influenced by RM composition (water content, solvent, surfactant), but the effect of encapsulated macromolecules on exchange dynamics remains underexplored. In this study, we measure kex by monitoring the fluorescence kinetics of a highly fluorescent chelate formed between terbium (III) chloride and dipicolinic acid within RMs. Using surfactants with varying headgroup charge distributions—anionic sodium bis(2-ethylhexyl) sulfosuccinate (AOT), cationic cetyltrimethylammonium bromide (CTAB), and a nonionic/zwitterionic mixture (10MAG/LDAO)—we investigate the impact of encapsulated ubiquitin at different concentrations on kex. These findings not only advance our understanding of protein encapsulation effects on RM dynamics but also represent the next step in optimizing delivery systems for protein-based therapeutics. Furthermore, they pave the way for potential kinetic release experiments, where the release profile of encapsulated proteins can be directly measured under different RM conditions. This study lays the groundwork for a predictive model of RM exchange, enabling fine-tuning of exchange rates based on RM composition and encapsulated cargo.

17 Rosalind Moore

PhD in Complex Biological Systems

Advisor(s): Matthew Farber

Title: RM06-A, a novel Lachancea yeast species isolated from pinelands habitat

Abstract: The Pine Barrens of New Jersey is a rare habitat, consisting of acidic, nutrient-poor soils with frequent disturbances from forest fires. The community of organisms that inhabit this area is uniquely adapted to survive in these conditions and are infrequently found outside a pinelands habitat. Previous research suggests there is a wealth of unidentified fungal species within this region. During sampling of yeast associated with Pinus rigida (pitch pine), an isolate (RM06-A) was collected and later found to be closely related to Lachancea lanzarotensis (TT Y-63768). Morphological and biochemical assays were coupled with genomic and sequencing data to observe phenotypic and molecular differences between RM06-A and the L. lanzarotensis type strain. Differences include colony morphology, cellular morphology, sporulation capability, and sugar assimilation. Analysis of the genomic sequence further supports RM06-A as a novel Lachancea species to be proposed. Future directions of this work aim to expand our knowledge of pinelands’ fungi as well as an understanding of the relationship between RM06-A, and others like it, to determine the role of fungal communities during post-fire succession of a pinelands habitat.

18 Frederick Nitchie

Ph.D in Clinical Psychology

Advisor(s): James Haugh

Title: Mindfulness, Social Problem-Solving, and Rumination: Predicting Unique Variance in Depression

Abstract: Mindfulness and social problem solving (SPS) have both been found to differentially predict symptoms of depression. Additionally, rumination has been found to correlate with depression as well as mindfulness, and social problem-solving. However, what remains unknown is how much unique variance rumination can explain in depressive scores when modeled alongside either mindfulness or SPS. Generalized linear modeling showed that ruminative thoughts significantly predicted unique variance in depression levels when tested alongside both mindfulness and SPS.

19 Nicholas Paradis

Pharmaceutical Chemistry

Advisor(s): Chun Wu

Title: Mutation Spectrum of ZIKV Genome suggests it follows Near Neutral Balanced Selectionist Theory (NNBST) as suggested by the substitution-mutation rate ratio test (c/µ)

Abstract: Zika virus (ZIKV) is a neuroinvasive flavivirus which causes neuroses in human infants and adults. Understanding the molecular evolution of ZIKV is critical for antiviral and vaccine development for ZIKV. In this study, we applied our substitution-mutation rate ratio (c/µ), where µ is rigorously approximated and independent of genetic codon tables and Markov mutation models, to elucidate the molecular evolution of ZIKV using empirical sequence data. c/µ is powerful to quantify the fractions of different mutation types at each nucleotide site in a genome, which we have previously demonstrated using SARS-COV-2 genomic sequence data. c/µ analysis revealed the ZIKV genome, Translated Region/TR and UnTranslated Region/UTR exhibited an L-shaped c/µ Distribution of Fitness Effects (DFE), substitution timelines exhibiting molecular clock and low percentage of strictly neutral mutations. These findings are inconsistent with conventional Neo-Darwinism Selectionist Theory/ST, Kimura’s Neutral Theory/KNT and Ohta’s Nearly-Neutral Theory/ONNT of molecular evolution but are consistent with Nearly-Neutral Balanced Selectionist Theory/NNBST, suggesting the balancing of nearly neutral mutations produce the molecular clock instead of strictly neutral mutations, challenging the core tenants of natural selection and genetic drifting mechanisms of evolution. The top mutations identified through c/µ > 1 are mostly consistent with their literature-reported adaptive and deleterious mutation effects. Molecular modeling of the top mutation effects identified through c/µ infers a reduced binding affinity of nucleotide analogs on NS5 polymerase, providing insights into ZIKV drug development. These findings provide additional support to the c/µ test in probing viral evolution and to explaining the genotype-to-phenotype relationship in species evolution.

20 Krishna  Paul

MS in Pharmaceutical Sciences

Collaborator(s): Na, Jesse

Advisor(s): Lark J. Perez

Title: Development of an Ensemble Biosensor for Fatty Acids

Abstract: Biosensors are devices with the ability to sense a specific binding molecule. An ensemble biosensor can bind multiple types of molecules which makes it an essential tool in diagnostics and biomedical research. Our ensemble biosensor system is capable of simultaneously detecting multiple fatty acids through protein-fluorophore interactions. A comprehensive fluorescence matrix was developed using three fluorophores—1-Anilinonaphthalene-8-Sulfonic Acid (1,8-ANS), 2-anthracene carboxylate (2AC), and Fluorescein—paired with proteins such as Bovine Serum Albumin (BSA) and Human Fatty Acid Binding Proteins (FABP-1, 2, 3, and 4). These fluorophore-protein complexes were introduced to eight distinct fatty acids in 96- and 384-well plates, with their fluorescence responses measured using a spectrometer.

The system operates on the principle that fluorophores emit light at specific wavelengths, which shifts upon binding to target molecules. When fatty acids bind to the corresponding protein, the fluorescence intensity changes, allowing for both detection and quantification. To interpret the complex fluorescence data, Principal Component Analysis (PCA) and Non-metric Multidimensional Scaling (NMDS) were applied to identify unique fluorescence patterns corresponding to each fatty acid.

Among the fluorophores tested, 1,8-ANS showed the highest consistency and reliability in fluorescence responses. The ensemble biosensor system accurately distinguished the eight fatty acids, achieving a PCA score of 94.59%, demonstrating high sensitivity and specificity for molecular identification.

The ensemble biosensor was further validated by analyzing human stool samples from patients with Helicobacter pylori infections and healthy controls. The ensemble biosensor system successfully differentiated between patient and control samples reflecting its potential to detect infection-related metabolic shifts.

Overall, this ensemble biosensor system demonstrates strong potential for multiplex fatty acid detection and could serve as a valuable diagnostic tool for gastrointestinal diseases, particularly those associated with H. pylori and other chronic diseases.

21 Hadarou Sare

PhD in MSE

Advisor(s): Dr. Dongmei Dong

Title: Thermodynamic Analysis and Mathematical Modeling of Asteroid Optical Mining Systems: Investigating Behaviors of Modeled Bag, Extracted Volatiles, and Sample

Abstract: This study advances the thermodynamic analysis of an asteroid optical mining system. This study also established new mathematical equations tailored to asteroid optical mining. This study is build upon our previous research where we modeled and design a high-strength and high-temperature-resistant bag made up of composite materials for asteroid mining. In this work, we integrate the asteroid mining bag into a deep-space optical mining system and investigate its thermodynamic behaviors. Utilizing MATLAB Simulink and the Simscape toolbox, we modeled the asteroid optical mining system and simulate the thermodynamic behavior of the bag, the sample (asteroid), and the extracted volatile materials. In our MATLAB Simulink model, we incorporated the thermodynamics equations from the literature. However, our results indicate that existing thermodynamic equations from the literature do not fully capture the heat dynamics specific to asteroid optical mining. To address this, we develop a solar thermal oven simulator and use it to derive new thermodynamic equations tailored to asteroid optical mining environment. Our solar thermal oven simulator is modeled using MATLAB Simulink and Simscape toolbox. This model is then used to conduct multiple simulations which help us to establish new thermodynamics equations applicable to asteroid optical mining environment. These newly formulated equations, including those for conductive heat flux, heat required to outgas an asteroid, thermal time constants, and outgassing dynamics, are validated through iterative simulations and integrated into our optical mining Simulink model we developed. These newly formulated equations are incorporated into our Simulink model. The refined simulation tool enables a more accurate assessment of the thermodynamic behaviors of the modeled bag, the extracted volatile materials, and the sample (asteroid) within the optical mining system. The temperatures, pressures, and stresses distributions within the mining bag and surrounding volatile materials during extraction are therefore established. This work contributes to the fundamental understanding of thermal interactions in asteroid mining and provides a framework for optimizing future in-space resource utilization technologies 

22 Bamidele Towolawi

PhD in Pharmaceutical Chemistry

Advisor(s): Drs. Zhiwei Liu and Zhihong Wang

Title: Exploring Protein-Protein Interaction Dynamics of the HVR Region of RAS Isoforms and the BSR Region of BRAF: A Molecular Dynamics Simulation Study

Abstract: Ras isoforms share a conserved GTPase domain but differ in their C-terminal hypervariable region (HVR), enriched with polybasic residues that facilitate interactions with membrane receptors, the G-domain, and other proteins. Activation occurs when GTP binding transitions Ras from an inactive GDP-bound state to an active GTP-bound state, initiating the RAF-MEK-ERK signaling cascade. RAF proteins, particularly BRAF, are central to this pathway, with dimerization playing a critical role in its activation. Previous studies in our lab demonstrated that BRAF exhibits isoform specificity toward KRAS. We hypothesize that this specificity arises from electrostatic interactions between the highly acidic BRAF-specific region (BSR) in BRAF’s N-terminal and the lysine-rich polybasic HVR of KRAS.

23 Manobin Sharma

PhD in Material Science and Engineering

Advisor(s): Dongmei Dong

Title: Operando Electrochemo-Mechanical Studies of Electrochromic Thin Solid Films Using AFM Microcantilever Electrodes

Abstract: "In this study, understanding of induced mechanical responses in energy storage applications. We correlate the charge injection and mechanical deflection in thin films and investigated how electrochemical cycling affects deflection and resonance frequency variations in coated versus uncoated AFM microcantilevers. On comparison of observed phenomenon, this study will provide insights into the storage of charge that will help on electrode design. We examined nickel oxide (NiO)-coated microcantilevers immersed in lithium perchlorate (LiClO₄) and platinum (Pt)-coated cantilevers in a ferri/ferrocyanide solution. The microcantilevers were fabricated with conductive coatings and configured as working electrodes in an electrochemical setup.  The current-potential response was recorded on the basis of applied potential and also induced deflection, and resonance frequency shifts. Characterization involved in situ AFM measurements to track deflection and frequency changes under applied potential. Control experiments showed results, with uncoated cantilevers were attributable to the charge storage material. Findings revealed that both the coated and uncoated cantilevers experienced deflection, but the coated cantilevers exhibited significantly higher deflection. Additionally, resonance frequency shifts on increasing with applied potential were observed in the coated cantilevers, whereas for uncoated cantilevers it remained unchanged. These results provide deeper insight into charge storage phenomenon and electro-chemo-mechanical coupling in thin films. The findings contribute to the development of advanced electrode materials with improved mechanical stability and charge storage efficiency for energy applications."

24 Mst Afroza Alam Tumpa

MS in Pharmaceutical Sciences

Collaborator(s): Tumpa, Mst Afroza Alam; Jimenez, Alida Maria

Advisor(s): Job, Martin O

Title: A Comparative Analysis of the Current Punishment Model and a New Quantitative Punishment Model for Sucrose/METH Self-Administration in Male and Female Rats Introduction

Abstract: We propose a Quantitative Punishment Model with Clustering (QPMC) to address the limitations of the current punishment model in differentiating shock-resistant (SR) and shock-sensitive (SS) subjects. QPMC clusters multiple behavioral variables, eliminating subjective endpoints used in the current model. We present evidence demonstrating the superiority of QPMC over the current punishment model in subjects self-administering sucrose pellets as a natural reward.

 Methodology

 Male and female Long Evans rats (n=15 males, n=16 females for the sucrose study; n=4 males, n=4 females for the METH study) underwent an initial pain sensitivity test. The animals were then allowed to self-administer sucrose pellets or METH on a fixed-ratio 1 schedule for 6 hours daily over 4 weeks. A second pain sensitivity assessment was conducted to evaluate the impact of prolonged sucrose intake on pain sensitivity. Following this, the rats were subjected to a punishment regimen with increasing footshock intensities from 0 to 1mA in 0.1mA increments. After a one-week recovery period, the animals underwent a third pain sensitivity test to assess the overall impact of the procedure. Rats were then perfused 19 to 25 days later. The current model used a 30% suppression in sucrose levels at 0.4mA as the separation criterion, whereas the QPMC model clustered multiple behavioral variables.

 Results

 The current punishment model identified 27 SS and 4 SR sucrose-administering rats, with no significant sex differences between the groups.

The QPMC model identified two clusters: Cluster 1 (n=23) and Cluster 2 (n=8), also without sex differences. Unlike the SS and SR classification, the clusters differed significantly across all behavioral variables tested.

Data analysis for METH-administering rats is ongoing.

 Conclusion

 Our findings indicate that QPMC is a more conservative and effective identification tool than the current punishment model.

25 Nakoa Webber

PhD in Complex Biological Systems

Advisor(s): Nathaniel Nucci

Title: Structure-function relationships of sigma receptors for therapeutic targeting

Abstract: Sigma receptors are non-opioid, transmembrane proteins with implications across a broad variety of cell functions and disease states. They are a desirable drug target for their roles in opioid mediated analgesia, cancer, and neurological disorders. Sigma receptors facilitate physiological and pharmacological processes through interactions with g protein coupled receptors (GPCRs), ion channels, and additional cell signaling factors. While agonists and antagonists have been identified to alter sigma receptor function, they are most frequently described using animal models without a known molecular mechanism. Both sigma-1 and sigma-2 receptors are found in various oligomeric states and we are interested in how ligand binding affects these structural changes. We will utilize structural biology methods to identify and monitor the stability of oligomerization states upon ligand binding to purified S1Rs and S2Rs. We look to characterize how structural changes relate to ligand classification and how these changes influence sigma receptor protein-protein interactions. Sigma-1 and Sigma-2 were cloned into a pcDNA3.1- plasmid vector and overexpressed in inducible expi293 cells. We have purified the sigma-1 receptor and will characterize oligomerization upon ligand binding through techniques such as size exclusion chromatography and thermal shift assays. By characterizing ligand binding effects on oligomerization as well as sigma protein-protein interactions, we will improve our overall understanding of sigma receptor biology.

26 Abigail White

PhD in Complex Biological Systems

Advisor(s): Melissa Manners

Title: Kappa opioid receptors response to inflammation in astrocytes and microglia: implications for stress-related disorders

Abstract: Chronic stress results in a pro-inflammatory response and can yield serious health consequences, including major depressive disorder (MDD) and substance use disorder (SUD). Given the high prevalence of chronic stress and the common comorbidity of MDD and SUD, understanding shared molecular factors underlying the development of these disorders may lead to improved therapeutics. The opioid system plays a crucial role in the behavioral stress response, and kappa opioid receptors (KORs) are dysregulated in patients with MDD and SUD. Furthermore, astrocytes and microglia are key inflammatory modulators of the central nervous system and respond to chronic stress. This study investigates the cellular expression of KORs in response to inflammation. Astrocytes and microglia were treated with lipopolysaccharide (LPS) for 4 or 24 hours to induce an inflammatory response. The data thus far suggests that LPS treatment increases KOR expression in microglia, with a more pronounced increase after 24 hours. In contrast, astrocytes exhibit a decrease in KOR expression after 4 hours, with no change following 24-hour treatment. These findings suggest that KORs response to inflammation is both cell type- and time-dependent.

27 Dawn Williams

PhD in Complex Biological Systems

Advisor(s): Maggie Pearce

Title: Determining Roles of Phosphorylated Rab10 in Huntington’s Disease

Abstract: Huntington's disease (HD) is a genetic disorder resulting in expansion of a polyQ stretch encoded by exon 1 in the huntingtin (HTT) gene. This mutation causes mutant huntingtin (mHTT) proteins to misfold and aggregate in vulnerable cells of the central nervous system. Accumulating evidence supports the hypothesis that protein aggregates associated with many neurodegenerative disorders, including Alzheimer’s disease (AD), Parkinson’s disease (PD), and HD, spread through the brain with properties similar to infectious prions: they can travel between cell cytoplasms and template the aggregation of soluble versions of the same protein. 

Our lab has reported that mHTT aggregates transfer between synaptically-connected neurons via obligatory glial intermediates in adult Drosophila melanogaster brains. The conserved scavenger receptor, Draper/MEGF10, is required for this process, suggesting that neuronal mHTT aggregates are engulfed by phagocytic glia via Draper-dependent phagocytosis, but that some engulfed aggregates escape from the phagolysosomal network to seed aggregation of natively-folded wild-type HTT (wtHTT) proteins. Forward genetic screening for intracellular proteins that mediate spread of mHTT aggregates from neurons to glia revealed Rab10, a small GTPase with emerging roles in vesicle maturation and trafficking in endocytic and phagocytic pathways. Intriguingly, Rab10 is a well-known phosphorylation target of leucine-rich repeat kinase 2 (LRRK2), variants of which are associated with increased risk of PD. Some PD-associated LRRK2 variants have elevated kinase activity, increase phosphorylation of Rab10 and other Rab GTPases, and are associated with lysosomal dysfunction and damage. The overarching goal of this project is to elucidate roles for Rab10 and LRRK2 in phagocytic engulfment and spreading of mHTT aggregates. The overall hypothesis I will test is that Rab10 and its phosphorylation by LRRK2 regulate propagation of mHTT in the brain. This overall hypothesis will be tested using Drosophila and cultured mammalian cells.

28 Jacob Zangaro

Ph.D in Pharmaceutical Chemistry

Advisor(s): Nathaniel Nucci

Title: Effects of Confinement and Quinary Interactions on Protein Stability

Abstract: The majority of thermodynamic studies of protein stability have been performed in dilute aqueous solution. The intracellular milieu, where most proteins function, presents an environment where high excluded volume and myriad interfaces conspire to complicate the thermodynamic landscape. Here, we use reverse micelles to better understand the interplay between (predicted) stabilizing effects such as confinement and (predicted) destabilizing effects of weak, non-specific interfacial binding. Reverse micelles (RMs) are spontaneously organizing nano-complexes that encapsulate a small aqueous core stabilized by surfactants dissolved in nonpolar solvents. Here, mixtures of decylmonoacyl glycerol (10MAG) with lauryldimethylamino-N-oxide (LDAO) or cetyltrimethylammonium bromide (CTAB) with hexanol were used to compare surfactant interfacial chemistries under comparable confinement conditions. Both surfactant systems have been proven to effectively encapsulate proteins while preserving their native conformations. 10MAG/LDAO produces a minimally charged interface whereas CTAB results in a positively charged interface. The model proteins myoglobin, cytochrome c, and flavodoxin were encapsulated and their folding or unfolding measured by fluorescence spectroscopy and/or nuclear magnetic resonance (NMR). We present comparative analysis of the RM influence on stability, including the process of unfolding for flavodoxin. We find that the effects are protein-dependent, yet we are able to quantify free energy differences due to interfacial interactions exclusive of confinement effects. Furthermore, we find that the measured differences depend on the denaturant used, providing insight into the nature of the unfolded state.

29 Ariel Zhang

PhD in Complex Biological Systems

Advisor(s): Melissa Manners

Title: Investigating Morphology and Activation of Microglia Via Chronic Stress - Induced neuroinflammation in the Brain

Abstract: Neuroinflammation has been associated with the development of chronic stress-related disorders. However, the detailed mechanism that links chronic stress to neuroinflammation is still unclear. As a primary mediator of the immune response, the activation of microglia serves as an indicator of the inflammation in the brain. In this study, we investigated the role of microglia activation due to the effect of chronic stress. We utilized the unpredictable chronic mild stress (UCMS) paradigm to induce chronic stress and conducted the light dark test (LDT) to evaluate the effect of chronic stress behaviorally. To analyze the activation of microglia at a cellular level, we quantified the morphological changes of IBA1 positive microglia in the prefrontal cortex (PFC), nucleus accumbens (NAC), hypothalamus (HYPO), amygdala (AMY), hippocampal CA1, and CA3. Chronic stress significantly increased behaviors associated with anxiety in males. Although no behavioral difference was observed in females, UCMS females exhibited reduced avoidance behaviors than UCMS males. To evaluate the activation of microglia, we quantified density, process length, and the number of processes in microglia. We did not observe a significant change in microglia density in the brain; however, chronic stress increased the number and length of the processes in microglia in region-specific and sex-dependent patterns. Notably, microglia from females exhibit morphologies that were more activated compared to males at the baseline in all brain regions. These findings suggest that females might have a higher inflammatory profile than males at the baseline, and this sex difference might contribute to the behavioral differences and the sex-specific mechanism of the diseases.

31 Liya Popova

PhD in Cell and Molecular Biology

Advisor(s): Valerie Carabetta

Title: THE ACETYLATION STATE OF HBSU AT LYSINE 41: A SIGNIFICANT REGULATOR OF GENE EXPRESSION DURING THE LATE STAGES OF BACILLUS SUBTILIS SPORULATION

Abstract: Sporulation is triggered by environmental stresses, such as nutrient starvation, resulting in the formation of highly resistant spores. It involves a complex series of reactions between the mother cell and the forespore, guided by sporulation-specific genes. It was proposed that the nucleoid-associated protein HBsu plays a role in chromosome compaction during the process of sporulation. Previously, we identified seven acetylation sites on HBsu. We examined the role of HBsu acetylation during sporulation, and  found a reduction in sporulation frequency and resistance properties of mature spores of mutant strains that mimic the acetylated forms (glutamine substitutions) of HBsu. We hypothesized that the DNA packaging or the gene expression program during sporulation might depend on the acetylation state of HBsu. To understand whether the acetylated forms of HBsu affect the sporulation program, we analyzed the expression of the sigma factor genes and their regulons, serving as reporters for their activity, using quantitative real-time PCR (qRT-PCR). Out of all seven mutants, we found that the hbsK41Q mutant significantly overexpressed the early sporulation genes (spo0A, spoIIGA, spoIIE, spoIIAB,spoIID, spoIIQ, sigF) at the T2 time point. In addition, the late sporulation genes (sigG, cotE, cotH, lipC, asnO, spoVK, spoIVCA, spoVT, spoVAA, sspB) were continuously overexpressed at both T2 and T4, compared to wildtype. Since we observed overexpression of sigF and sigG mRNA, we analyzed their protein levels by western blot, and found overproduction of σF at both T2 and T4, and σG at T4.  We also detected overexpression of the reporters for σK activity (late sporulation genes cotE, cotH, cotD, and lipC) at T2 and T4, and an increase in SigK protein levels at T4. Contrary to hbsK41Q, the opposite mutant mimicking the deacetylated state, hbsK41R, did not show a difference in the expression of the above-mentioned genes. Our findings suggest that the acetylation state of HBsu at K41 is critical for proper gene expression during sporulation. We propose that it regulates the transition between early and late sporulation phases, and that  deacetylation of K41 is necessary to turn off expression of specific genes during the lates stages of sporulation.

32 Victoria Young

Postdoctoral Fellow

Advisor(s): Susy Kohout

Title: Investigating Voltage-Sensing Phosphatase Function in Brain and Kidney Tissues Using a Knockout Mouse Model

Abstract: Cells rely on electrical and chemical signals to function. The voltage-sensing phosphatase (VSP) (Tpte2) is a unique protein that couples the chemical signaling of a 3 and 5  phosphatidylinositol phosphate (PIP) phosphatase to the electrical signaling of a voltage sensor domain. VSP is expressed in the apical membrane of kidney tubules and cortical neurons; however, its function in these tissues is unknown. Because of the apical expression of VSP in kidney tubules, we hypothesize that the lack of VSP would impact the reabsorption of small molecules and electrolytes. We analyzed the blood serum and urine of VSP knockout (KO) mice in comparison to wildtype (WT) mice. Preliminary results from 4–6-week-old mice (adolescent) and 7–11-week-old mice (young adult), showed no change in serum (albumin, phosphorous, creatinine, BUN, chloride and sodium) levels and no change in urine (creatinine, chloride, and sodium) levels. This lack of functional effects could be caused by compensational changes in gene expression; therefore, we have sent kidney tissue for RNA sequencing. Preliminary analysis in the VSP-KO shows gene pathways enriched in genes related to targets of E2F transcription factors. Individual genes are still being analyzed, but the sodium-coupled citrate transporter (Slc13a2) shows a decreased expression in VSP-KO. Lack of global effects makes us hypothesis that VSP-KO in the cortical neurons will cause changes on the cellular level, impacting neuronal firing by channel functioning. We are culturing primary mouse cortical neurons and are in the process of transfecting PIP biosensors to measure PIP concentration changes, and patch clamping to measure neuronal firing. Simultaneously, we are preforming RNA sequencing of cortex tissue. VSP-KO shows enrichment in genes related to epithelial mesenchymal transition. In conclusion, while this research is ongoing, it will ultimately provide a greater understanding of how PIP changes affect function in kidney and brain tissues.

33 Catherine  Alapatt

Doctorate of Osteopathic Medicine

Advisor(s): Andrea Bottaro

Title: Accelerated tumor growth and lymphatic spread of transplantable melanomas in Tumor Necrosis Factor(TNF)-transgenic mice

Abstract: Melanoma is the fifth most common cancer among American adults, with significant morbidity and mortality at 5 years remaining >60% for patients with stage IV disease. The malignancy is due to the transformation of melanocytes, with one of the major risk factors being ultraviolet light exposure. Although as many as one in five human cancers have been linked to chronic inflammation, the role of inflammatory signals in melanoma growth and metastasis remains poorly understood. 

Tumor necrosis factor (TNF)-transgenic (TNFtg) mice are a well-established model of chronic systemic inflammation, with involvement of joints and other organ systems.  To assess the effect of TNF overexpression on melanoma in vivo, we investigated the growth of transplantable B16 melanomas (F1 and F10 sublines) in TNFtg mice (3647 strain). The B16 cell line and its derivatives originated from a spontaneous melanoma of C57BL/6 mouse. B16 cells were injected into the hind paws of TNFtg mice and non-transgenic (NT) littermates at 8-12 weeks of age. At this age, the mice have begun to exhibit early arthritis, creating a localized area of inflammation in the paw. TNFtg mice displayed highly accelerated B16 primary tumor growth compared to NT littermates (tumor area 43.7±15.2mm2 vs 15.0±15.5mm2 at week 2, p<0.001), and early tumor-draining lymph node (TDLN) invasion (14/31 vs 7/34 positive TDLNs in TNFtg vs NT mice, p<0.05). No significant differences were observed between F1 and F10 tumors, or male vs female mice. 

To test whether the observed effects were linked to systemic TNF overexpression or to the localized inflamed microenvironment in the arthritic paws we also compared growth of tumors injected in the lower flank, and observed no primary tumor growth differences in this area (251±155mm3 vs 319±178mm3 tumor volume in TNFtg vs NT, p=0.3). 

Finally, in order to establish whether the observed differences were specific to B16 cells or are relevant for melanoma growth more broadly, we compared growth in TNFtg vs NT mice of an independently derived melanoma line, YUMM1.1.  Again, TNFtg mice showed accelerated paw melanoma growth compared to NT mice (32.6±14.0mm2 vs 19.1±20.8mm2 at week 5, p<0.01).

Overall, these results highlight a significant effect of TNF, and specifically of the TNF-driven inflammatory microenvironment, in transplantable melanoma growth in mice.

30 Md Redwan Sammir

PhD in ECE

Collaborator(s): Casas., Tyler Philip; Kang, Jim S.

Advisor(s): Dr. Jie Li, Dr. Thanh Trung Nguyen, Dr. John L. Schmalzel

Title: IFROST MAPPER: Multi-Frequency Electromagnetic Induction (MFEMI) Technology for Geophysical Characterization of Soils in Cold Regions

Abstract: The presence of permafrost or frozen soil, the current cold-region infrastructure development, and climate change have major implications in geohazards: ground subsidence/destabilization, flooding, etc. As such, geophysical characterization is vital for site investigation and the detection of potential hazards. Multi Frequency Electromagnetic Induction (MFEMI) technology is proposed for geophysical characterization of soils in cold regions to assist in DoD missions. High resolution, multi-scale geophysical characteristics of frozen soils are investigated using electrical and electromagnetic measurements, collected by a portable and cost-effective MFEMI device. This technology is especially useful for surveying massive amounts of land for permafrost deposits in cold regions. To accurately characterize the geophysical properties of soils from EMI data, a robust inversion algorithm is required. Building on this research objective, the IFROST MAPPER aims to design and develop the MFEMI hardware, MFEMI data inversion algorithms, and methods for geomaterials characterization of frozen soils. This project is an interdisciplinary collaboration between project team researchers from Electrical Engineering, Civil Engineering, and Mathematics in tackling this challenging problem.

99 Christopher Acquah

PhD in Chemical Engineering

Title: Self-Sustaining Biorefinery of Spent Coffee Grounds for 100% Drop-In Sustainable Aviation Fuel (SAF)

Collaborator(s): Wo Bin Bae, Kylie Howard, Ishimiah Small, Jack Kleissler, John Pazik, Nathaniel Holl, Brian Ramirez

Advisor: Jun Hee Jang

Abstract: 

The aviation sector significantly contributes to global CO₂ emissions, which are expected to double by 2050. Sustainable Aviation Fuels (SAF) offer the most viable near-term solution for reducing these emissions. This research develops a self-sustaining biorefinery that produces 100% drop-in SAF from spent coffee grounds (SCG), an abundant and renewable feedstock.  Two novel fractionation technologies were introduced: an alcohol-based solvolysis and a hexane-water biphasic system. These methods effectively separate triglycerides, carbohydrates, and lignin, optimizing their conversion via hydroprocessed esters and fatty acids (HEFA), alcohol-to-jet (ATJ), and hydrodeoxygenation (HDO) pathways, respectively. Integrated product recirculation eliminates external solvents, significantly enhancing sustainability and cost-effectiveness.  Catalytic upgrading demonstrated efficient conversion to SAF-compliant hydrocarbons.  Preliminary techno-economic and life-cycle assessments confirm the biorefinery's scalability, economic feasibility, and environmental benefits. This innovative approach significantly advances aviation decarbonization efforts.

34 Moayad Al Issa

MS

Advisor(s): Yusuf Mehta

Title: Impact of Softening Agents on the Rheological Performance of Highly Elastic Asphalt Binders

Abstract: Low temperature cracking in cold regions highlighted the necessity of producing asphalt binders that can perform against traffic and environmental conditions. Highly Elastic Asphalt Binders (HEBs) are such binders that can exhibit superior performance in extreme low temperatures The current study evaluates the rheological performance of HEBs produced using two control binders (PG 52-28 and PG 64-22). A high styrene-butadiene-styrene (SBS) polymer content of 7.5% by weight of binder and two types of softening agents with different dosages were adopted for the research evaluation. HEBs were tested for their storage stability and for morphological characteristics. The linear viscoelastic rheological behavior was assessed using master curves of complex shear modulus (G*) and phase angle (δ). Low-temperature performance was evaluated using the Bending Beam Rheometer (BBR) test. Rutting and fatigue performance was assessed using multiple stress creep and recovery (MSCR) test and linear amplitude sweep (LAS) test, respectively. Results show that binders modified with softening agents show improved storage stability. Fluorescence microscopy showed that binders modified with softening agents have a more homogenous, and less condensed polymer network distribution compared to high polymer-modified binders produced without any softening agents. Low-temperature cracking performance with corn oil-modified binders, have shown superior performance compared to hydrolene oil-modified asphalt binders. Delta Tc (ΔTc) values indicate that stiffer control binders (PG 64-22) may not be applicable for the HEB modification approach.  HEBs showed enhanced fatigue resistance compared to the control binders. In summary, HEBs exhibited enhanced intermediate, and low-temperature performance, with marginal reduction in rut resistance making this approach suitable for practical asphalt applications in cold regions. 

35 Ruqaya Alfaris

PhD in Civil and Environmental Engineering

Advisor(s): Mohammad Jalayer

Title: Unpacking Transportation Equity: A Contemporary Literature Review and Qualitative Analysis

Abstract: This poster undertakes a systematic literature review to examine the concept of transportation equity, shedding light on its multilayered implications, challenges, barriers, and potential opportunities. Through keywords distribution, co-occurrence, and thematic analysis methods, the study delves into diverse aspects of transportation equity, ranging from accessibility to essential services such as education, healthcare, and jobs to its broader impacts on social inclusion, economic growth, health outcomes, environmental sustainability, and urban planning. The findings illustrate a complex interplay of factors that necessitate a holistic approach to addressing transportation inequity. Drawing on the results of co-occurrence and thematic analysis, the study provides a comprehensive overview of the prevailing challenges and barriers and highlights strategies to enhance transportation equity. Furthermore, this research highlights the need for future research to focus on designing equitable transport systems that cater to the needs of all, with a particular emphasis on vulnerable groups. This review thereby contributes to the existing body of literature by providing a consolidated understanding of transportation equity, paving the way for future research and policy-making in this area.

36 Ruqaya Alfaris

PhD in Civil and Environmental Engineering

Advisor(s): Mohammad Jalayer

Title: Exploring Road Safety Disparities and Crash Factors in Disadvantaged Communities

Abstract: Traffic safety is a critical public health issue that affects people of all ages, races, genders, and socio-economic backgrounds. This article investigates the contributing factors to traffic crashes’ severity in socially vulnerable areas and proposes evidence-based recommendations to reduce traffic safety disparities. The study utilizes the XGBoost machine learning model and SHAP value technique, employing crash data and the social vulnerability index established by the Centers for Disease Control and Prevention (SVI CDC) datasets as input. The analysis uncovers significant factors, including pedestrian involvement, limited transportation access, risky behaviors, and insufficient traffic safety education, that contribute to the higher severity levels of traffic crashes in socially vulnerable communities. To address these disparities, recommendations are made. These include improving infrastructure, promoting alternative modes of transportation, implementing comprehensive traffic safety education programs, and fostering collaboration among stakeholders. By implementing these measures, more equitable and safer transportation environments could be created, and secure and reliable transportation options could be ensured for everyone, irrespective of their socioeconomic status. This research underscores the importance of addressing traffic safety disparities and provides valuable insights for policymakers, transportation agencies, and community organizations seeking to promote traffic safety and equity in socially vulnerable areas.

37 Abdelrahman  Ali

PhD in Civil Engineering

Advisor(s): Yusuf Mehta

Title: Effect of Aggregate Properties on Abrasion Resistance of Airfield Pavements

Abstract: Abrasion resistance is a critical factor in ensuring the safety and operational efficiency of airfield pavements, particularly under varying weather conditions. The texture of the pavement surface, including macrotexture and microtexture, plays a significant role in controlling abrasion resistance. Therefore, appropriate selection of aggregates is critical in maintaining adequate abrasion resistance. The experimental plan of aggregate properties involved X-Ray Fluorescence spectrometry (XRF), Los Angeles Abrasion (LAA), Micro-Deval Abrasion (MDA), Pearson Correlation Coefficient analysis (PCC), and Multiple Linnear Regression analysis (MLR). The chemical compounds within the aggregates were obtained by XRF. The aggregate deterioration was evaluated using the LAA, and the MDA test measured the capability to resist wet environment abrasion. The PCC analysis was performed to correlate the chemical compounds, LAA mass loss, and MDA mass loss. Finally, the MLR analysis was developed to predict the MDA values for coarse aggregates. Results showed that the chemical compounds are an indication of the adequacy of the abrasion resistance potential of aggregates. The outcomes of the LAA showed that out of 45 stockpiles of varying sizes, 42% showed average LAA test values ranging from 20% to 30%. Only 29% of the aggregate sizes had average LAA test values below 20% mass loss and were considered to perform better in abrasion resistance. The findings of the MDA test for both coarse and fine aggregates were between 5% and 25%. However, aggregate sources with MDA test values averaging below 18% mass loss are considered acceptable in terms of wear resistance. Overall, the PCC analysis demonstrated a strong correlation between the combined minerals oxides with MDA resistance and LAA resistance variables. A statistical model was developed to predict the abrasion resistance of aggregates based on the chemical compounds, LAA mass loss, and MDA mass loss to identify the aggregates to be used in airfield pavements.

38 Yusuf Asad

PhD in Biomedical Engineering

Advisor(s): Dr. Ying (Grace) Chen

Title: A Novel Resorbable Metallo-Elastomer Vascular Graft with Integrated Cell Reservoir

Abstract: Cardiovascular diseases (CVDs) are the leading cause of death globally, which require effective vascular grafts. While autologous grafts are ideal due to their superior integration and lower complication rates, one-third of patients lack suitable donor vessels. Synthetic grafts made from materials like PET and ePTFE are often used but are associated with complications such as thrombosis, stenosis, and low patency rates, especially in small-diameter vessels (<6 mm). Therefore, there is an urgent need for advanced bioresorbable grafts that leverage the host's regenerative capacities for in situ arterial regeneration. In our current research, we seek to synthesize a new class of biodegradable metallo-elastomers and use them to engineer fully resorbable synthetic grafts with tunable degradation, mechanical properties, and biofunctions. Our hypothesis is that the host’s body is the most effective bioreactor for remodeling biodegradable vascular grafts. When material degradation aligns with neotissue formation, synthetic grafts can evolve into autologous conduits similar to native arteries. There are three main objectives this project. Objective 1: Design, synthesis, and characterization of biodegradable metallo-elastomers with tunable mechanical properties, degradation rates, and biofunctions. Objective 2: Engineer porous metallo-elastomer vascular grafts integrated with an endothelial progenitor cells (EPCs) reservoir. Objective 3: Evaluation of candidate vascular grafts in a rat carotid artery interposition model for in situ graft remodeling and arterial regeneration. Successful completion of this study will result in a synthetic vascular graft with mechanical properties and degradation rates that align with the in-situ regeneration rate. Additionally, the inclusion of an EPCs reservoir integrated into the ablumen of the graft will promote rapid early-stage luminal endothelialization and prevent thrombosis. Our ultimate goal is to address the urgent need for vascular substitutes that match the efficacy of autografts without their associated limitations.

39A Anil Kumar Baditha

Postdoctoral Fellow

Collaborator(s): Sk Md Imdadul

Advisor(s): Yusuf Mehta

Title: Influence of Polyethylene Characteristics on Volumetric Properties and Performance of Asphalt Mixtures

Abstract: The main goal of the study is to evaluate the influence of polyethylene (PE) source variability on the design air voids and performance of asphalt mixture. In this process, PEs from three different sources were collected and their thermal characteristics were captured using a Differential Scanning calorimeter (DSC). After identifying PEs in terms of Degree of Crystallinity (Xc) instead of source, plastic was incorporated in asphalt mixtures through dry mixing method as a replacement to asphalt binder at 3%, 6% and 9% by weight of asphalt binder. From air void and aggregate-PE coating assessment, PE with low Xc was observed to act as a binding agent while a PE with high Xc was found to act as a filler. In terms of performance, PE incorporation was effective in improving the rutting tolerance index (RTindex) at 58°C and tensile strength ratio of asphalt mixtures irrespective of Xc property. The cracking tolerance index (CTindex) at 19°C declined for PE with low Xc (60% and 65%) and enhanced for PE with high Xc (92%). However, Fracture energy (Gf) versus post peak parameter (l75/m75) plot conveyed that PE high low Xc imparted ductile behavior to the mixture, which facilitates the design of effective plastic modified mixtures against cracking. The fracture energy evaluated at -18°C using Disk Shaped Compact tension (DCT) test embodied the undesirable performance of PE modified mixtures at all Xc levels. Overall, identifying PE in terms of Xc rather than source can be a substantial way of predicting volumetric and performance of PE modified mixtures.

39B Anil Kumar  Baditha

Postodctoral researcher in Civi and Environemental Engineering Department

Collaborator(s): Ayyaz Fareed

Advisor(s): Yusuf Mehta

Title: Evaluate the Impact of Microencapsulated Phase Change Materials in Asphalt Binder with an Extended Thermoregulation Range

Abstract: Extended thermoregulation range of microencapsulated phase change materials (MPCMs) is necessary for improvement in the performance of asphalt binder across wide range of temperatures.  For this purpose, two MPCMs (melting points: 6°C and 28°C) were combined into M6+M28 (1:1) and these were blended into Base binders at dosages of 5%, 10%, and 20%. Then, samples were evaluated for thermoregulation range, long-term effective transfer, and survivability through thermal profiles and enthalpy ratios at different aging levels. Rheological validation involved percentage change in complex modulus (G*) and phase angle (δ). Performance of combined MPCMs within thermoregulation range was assessed using fatigue factors at PAV level, overall rutting resistance via G* and δ at RTFO, and overall fatigue cracking resistance through Glover-Rowe parameter. Results showed that M6+M28 at any dosage and binder type-controlled stiffness and viscoelastic properties within an extended range of -12°C to 33°C, compared to -12°C to 16°C and 10°C to 33°C for individual MPCMs. The thermal stability of combined MPCMs was found to be decreased with aging except in soft grade binders at higher dosages. Additionally, M6+M28 improved cracking performance within thermoregulation range for both PG 58-28 and PG 64-22 binders, though dosage impact varied. The Glover-Rowe parameter indicated improved fatigue cracking resistance at any dosage and both binder types, whereas rutting resistance enhanced only for PG 58-28 binders at any dosage.

40 Hoi Yan Yu

PhD in Biomedical Engineering

Advisor(s): Sophia Orbach

Title: Predicting Liver Toxicity Risk in Cancer Patients with Polypharmacy Using Machine Learning Approaches

Abstract: Background:

 Polypharmacy, the concurrent use of five or more medications, is prevalent in cancer patients and significantly complicates treatment outcomes. Among cancer patients, polypharmacy increases the risk of drug-induced liver injury (DILI), which is one of the leading causes of hospitalization and treatment failure. However, current drug-drug interaction (DDI) models are limited, often only considering two-drug combinations and lacking patient-specific biological and demographic factors. To address this gap, we are developing predictive models that integrate real-world patient data to assess liver toxicity risk in cancer patients undergoing polypharmacy.

 Methods:

 This study utilizes electronic health records (EHRs), medication histories, and genomic data to identify risk factors for DILI. Machine learning models, including Support Vector Machines (SVM), Random Forest, and deep learning techniques, are employed to analyze clinical and genetic predictors of liver toxicity. Specific patient phenotypic variables (e.g., age, sex, race, genetic variants, liver enzyme levels) will be integrated with medication exposure data to develop a predictive model for liver toxicity risk.

 Expected Results:

We anticipate identifying key predictors of DILI risk in different cancer patients undergoing polypharmacy, which may include specific drug combinations, genetic predispositions, and clinical markers. The integration of machine learning with real-world patient data will improve precision medicine approaches, enabling physicians to optimize treatment plans and reduce adverse drug reactions in cancer patients.

 Conclusion:

 This research highlights the potential of AI-driven clinical decision support tools in mitigating polypharmacy-related toxicities. By leveraging advanced computational approaches, we aim to provide a data-driven framework for safer and more personalized cancer therapies.

41 Ian Bain

MS in Mechanical Engineering

Advisor(s): Dr. Mitja Trkov and Dr. Mehmet Uygur

Title: Evaluating leg asymmetry using kinetic and muscle activation variables during squat jumps

Abstract: This project is a cross-department collaboration between Mechanical Engineering and Health and Exercise Science at Rowan. The overall goal is to evaluate asymmetry between legs during squat jumps, using kinetic and electromyographic (EMG) variables. The first objective was to establish and validate a comprehensive kinetic and EMG data collection systems in the Biomechanics Lab to support current and future collaborative research on human movement studies. The second objective was to perform a small-scale experiment to ensure the data collection/analyses systems are valid. The setup involves two force plates and a 16-channel wireless EMG unit to collect synchronized kinetic and EMG data, respectively. The force plates were first calibrated, with 1%-2% margin of error. 10 wireless nodes from the EMG system were used, allowing for 5 muscles per leg to be analyzed. All data was collected at a sampling rate of 1000 Hz. Muscle asymmetry between legs was analyzed across three tasks: standing (stationary), squatting (dynamic), and squat jumping (explosive). Each foot was placed on a separate force plate to measure the ground reaction force, with EMG units attached to the medial and lateral gastrocnemius, vastus medialis, rectus femoris, and biceps femoris. Recorded force data and muscle activation data were then used to find peak forces, rate of force development, peak EMG signal, and rate of EMG rise in each leg. Results between each leg were compared to evaluate symmetry between legs. Both the kinetic and EMG results are consistent with the existing literature, ensuring the validity of the systems used in the lab. Based on the best knowledge of the authors, the results of muscle activations and the rate of EMG rise during squat jumps are novel and provide further insights into understanding of squat jump movement and potential leg asymmetries in subjects performing such movements.

42 Kebisha Basukala

PhD in Biomedical Engineering

Advisor(s): Sebastian Vega

Title: Peptide-Responsive Synthetic Receptors for Transcriptional Regulation in 3D Hydrogels

Abstract: EPDA (Extracellular Peptide-ligand Dimerization Actuator) is a synthetic transmembrane receptor engineered in the Vega Lab, designed to sense and respond to peptide-ligands in 3D hydrogels. Upon extracellular ligand binding, an intracellular phosphorylation event triggers the fusion of two split protein halves. As proof-of-concept, we demonstrated a peptide-ligand dose and temporal response by measuring the fusion of green fluorescent protein (GFP) halves via confocal microscopy and flow cytometry. While our first-generation EPDA employs split fluorescence as an activation indicator, our second-generation EPDA aims to drive cellular transcription in response to peptide-ligand activation.

 In this updated platform, ligand-induced merging of a transcriptional complex results in its nuclear translocation and subsequent transcription of Yellow Fluorescent Protein (YFP), confirmed by the intracellular YFP expression. To achieve this, we designed plasmids incorporating key components for transcriptional activation, including a DNA-binding domain, an effector protein (VP64), and an SH2 domain. Human embryonic kidney (HEK293) cells were transfected with these constructs and encapsulated in 3D hydrogels. Post-encapsulation, the hydrogels were photopatterned with activating and rhodamine peptides to confirm pattern localization. Using confocal microscopy, transcription (as confirmed by YFP) was evaluated inside and outside peptide-patterned regions.

 This approach presents a controlled mechanism for regulating transcription in response to external stimuli, with potential applications in tissue engineering and regenerative medicine. For example, EPDA receptors could be designed to induce bone differentiation in response to peptide-ligand activation within 3D hydrogels, offering a novel strategy for tissue regeneration. The receptor’s novelty lies in its targeted activation, orthogonal signaling, and ability to drive precise transcriptional responses within biomaterial environments, making it valuable for various therapeutic applications.

43 Brett Boyle

4+1 MS in Materials Science (Boyle, Brett); PhD in Mechanical Engineering (Das, Bably)

Collaborator(s): Boyle, Brett; Das, Bably

Advisor(s): Behrad Koohbor

Title: Fabrication and Characterization of Thermoformed Auxetic Foams

Abstract: The emerging interest in polymeric foams has led to the fabrication of auxetic foam that possesses a negative Poisson’s ratio. This kind of foam provides outstanding mechanical and energy absorption properties which makes them applicable for the impact mitigation application in comparison with non-auxetic and regular foams. Our current study aims to determine the critical compression ratio leading to the newly manufactured auxetic foam along with the thermal treatment protocols using a three-step thermoforming process. Critical compression ratio is first identified by the quasi-static compression tests in conjunction with 2D digital image correlation (DIC) on as-received elastomeric foams. Then, the global strains corresponding to the maximum energy absorption ideality, maximum efficiency and minimum Poisson’s ratio are identified. The foam samples are then compressed within a custom mold with lateral confinements and then heated at elevated temperatures to facilitate thermoforming. The mechanical characterization of the heat-treated foams after removing from the fixture yields a new set of engineering stress-strain and Poisson’s ratios. The obtained results are then used to compare the Poisson’s ratio and other load bearing metrics. Our preliminary results suggests that the novel thermoforming process designed here is a facile and effective approach to adjust and improve the impact mitigation properties in elastomeric foams.

44 Brittany Butler-Morton

PhD in Engineering Education

Advisor(s): Cheryl Bodnar

Title: Bridging the Theory-to-Practice Gap in Process Safety: Examining Judgment Differences Between Senior Chemical Engineering Students and Industry Practitioners

Abstract: Process safety management is vital to companies operating with highly hazardous materials or processes, consequently leading to a large emphasis on safety in engineering classrooms. However, process safety judgments are often influenced by a variety of competing criteria such as interpersonal relationships, budget, production, and leadership that are not emphasized sufficiently as part of current instructional practice. Case studies are commonly used ways of teaching process safety, however, they lack the immersion that would expose students to the full extent of the judgment making process leaving students not as well prepared for the situations they will encounter when working within industry. The Theory-to-Practice gap defines the time it takes for engineering students to adapt to their new workplace and become effective contributors. This gap occurs when complex and fundamental concepts are taught through simple, context-free problems in an educational setting. While the Theory-to-Practice gap has been studied in many areas of engineering, little work has been done to address it in the field of process safety. The aim of this work is to identify and understand if there are any differences in how senior chemical engineering students and industry practitioners make process safety judgments and apply these learnings to create process safety instructional methods that may potentially advance senior chemical engineering students’ skills acquisition. 

45 Ethan Cantor

PhD in Electrical and Computer Engineering

Advisor(s): Dr. Jie Li

Title: Advanced Capacity Accreditation for Improved Power System Reliability

Abstract: New Jersey and the broader U.S. electrical grid are undergoing a significant transition as fossil fuel power plants are replaced by emissions-free renewable generation, such as solar photovoltaics and onshore/offshore wind farms. While environmentally beneficial, the intermittent and non-dispatchable nature of these resources poses challenges to grid reliability and security. To ensure the long-term reliability of New Jersey’s and the nation’s bulk electric system, it is crucial to reassess how renewable resources contribute to capacity planning. The industry-standard method for calculating generation capacity contributions, Effective Load Carrying Capability (ELCC), has limitations. The current approach tends to underestimate the contributions of renewable resources, leading to excessive capacity procurement and increased costs for consumers. Additionally, it does not adequately account for extreme weather conditions, renewable resource variability, or locational and transmission constraints. This work proposes an enhanced ELCC methodology that integrates these factors, providing a more accurate and holistic assessment. By incorporating natural resource availability and network constraints, this approach aims to equip system operators with better tools for ensuring future grid reliability and security.

46 Mohit Chaudhary

PhD in ECE

Collaborator(s): Rostami, Mohammad

Advisor(s): Yusuf Mehta

Title: Influence of Nano-Modifiers on Healing and Fatigue Properties of Asphalt Binders

Abstract: This study focuses on evaluating the impact of nanomodifiers on the healing and fatigue properties of asphalt binders. Nanomodified binders were created by incorporating three types of nanomaterials—nanoclay, nanosilica, and nanoalumina—into PG 58-22 and PG 76-22 binders at dosages of 1%, 3%, and 4% by binder weight. The fatigue life of the binders was assessed using the conventional linear amplitude sweep (LAS) test, determining the number of cycles to failure at 2.5% strain. The self-healing potential of the nanomodified asphalt binders was examined using the LAS Healing (LASH) test, which involved varying rest periods (10, 20, and 30 minutes) and damage levels (25%, 37.5%, and 50%). Results indicated that nanoclay exhibited the best performance, followed by nanosilica and nanoalumina. Additionally, the healing ability of the binders improved with the introduction of rest periods of 10 and 20 minutes but declined beyond this duration. A damage level of 25% was found to be the most effective for incorporating rest periods, representing the micro-damage zone. Ultimately, nanoclay at a higher dosage (4%), combined with a 20-minute rest period and a 25% damage level, was identified as the optimal combination for enhancing self-healing in asphalt binders based on the study's findings.

47 Atik Faysal

PhD in ECE

Advisor(s): Huaxia Wang

Title: DenoMAE2.0: Improving Denoising Masked Autoencoders by Classifying Local Patches

Abstract: We introduce DenoMAE2.0, an enhanced denoising masked autoencoder that integrates a local patch classification objective alongside traditional reconstruction loss to improve representation learning and robustness. Unlike conventional Masked Autoencoders (MAE), which focus solely on reconstructing missing inputs, DenoMAE2.0 introduces position-aware classification of unmasked patches, enabling the model to capture fine-grained local features while maintaining global coherence. This dual-objective approach is particularly beneficial in semi-supervised learning for wireless communication, where high noise levels and data scarcity pose significant challenges. We conduct extensive experiments on modulation signal classification across a wide range of signal-to-noise ratios (SNRs), from extremely low to moderately high conditions and in a low data regime. Our results demonstrate that DenoMAE2.0 surpasses its predecessor, DenoMAE, and other baselines in both denoising quality and downstream classification accuracy. DenoMAE2.0 achieves a 1.1\% improvement over DenoMAE on our dataset and 11.83\%, 16.55\% significant improved accuracy gains on the RadioML benchmark, over DenoMAE, for constellation diagram classification of modulation signals.

48 Lakshmana Ravi Raj Gali

PhD in Civil and Environmental Engineering

Advisor(s): Prof Yusuf Mehta

Title: Evaluating Thermal Characteristics of Foam Glass Aggregates as an Insulation Layer in Asphalt Pavements

Abstract: Cold region pavements are subjected to extreme weather conditions that can cause structural failures like soil freeze-thaw and upheaval. Insulation materials such as extruded polystyrene boards (XPS), Foam Glass Aggregate (FGA) and Tire Chips (TC) are being used to mitigate these structural failures by thermally isolating the soil from the top pavement layers. Owing to structural issues of XPS, there is a need to identify sustainable alternative insulation material which can perform thermally and mechanically. Compaction becomes crucial as these materials (TC, FGA, FC) are structurally weak and moisture presence can alter thermal behavior. This study explores the thermal behavior of FGA as an insulation material under  different levels of temperature, moisture and compaction. Limited lab protocols currently use Thin Line Source (TLS-100) method to perform laboratory characterization, of FGA material. Hence, heat transfer based finite element (FE) simulation of TLS-100 was developed to estimate sample requirements like sample dimensions and dwell time, which is defined as time needed to reach a particular thermal steady state. Results yielded that thermal conductivity of FGA increased by 8 times with an increase in moisture content. Decrease in temperature and increase in compaction also effected thermal conductivity marginally. Sensitivity analysis using one at a time (OAT) approach revealed that the decreasing order of factors affecting thermal conductivity is moisture, temperature and compaction ratio. A second order response surface methodology-based model was developed which can predict thermal conductivity for a given climatic condition (moisture content and temperature). Statistical analysis revealed that two-way interaction between temperature and moisture content is not significantly affecting thermal conductivity above the freezing point.  Partial replacement of FGA with TC resulted in a stable compaction of FGA material than moisture addition.

49 Barnabas  Gao

PhD in Chemical Engineering

Advisor(s): Dr. Kirti Yenkie

Title: Computational Studies of Flushing Dynamics During Product Changeovers in Multi-Product Pipelines

Abstract: Product integrity is a crucial concern in the management of multiproduct pipelines in the oil and petrochemical industries. These pipelines, characterized by a complex network of interconnected pipes, are employed for the processing of a wide range of oil products with varying physical properties. A significant challenge in the operation of such pipelines is the changeover process, where residual oils from previous batches must be flushed out before introducing a new product. This process is complicated by the formation of a three-layered zone within the pipeline, consisting of the leading residual oils, a mixed section of blended oils, and the flushing oil at the forefront. The presence of these zones necessitates the use of large volumes of flush oil to effectively displace the residual and mixed oils, thereby impacting the efficiency and cost-effectiveness of the operation. This study presents a comprehensive experimental and numerical investigation of the flushing process in miscible but dissimilar oil systems using an industrial-scaled-down pilot plant. Our experimental approach utilizes targeted experimentation in the pilot plant for each product changeover category, which is devoid of sampling, due to the installation of an inline viscometer for online measurement of product viscosity. This setup allows for continuous monitoring of the flushing process and provides valuable data for validating and refining the numerical model. By combining experimental insights with the predictive capabilities of the model, we aim to develop an optimized flushing operation that minimizes the formation of mixed sections and reduces the volume of flushing oil needed for each product changeover.

The significance of this work lies in its potential to improve the operational efficiency and sustainability of multiproduct pipeline systems. By reducing the volume of flushing oil required, we can decrease operational costs and minimize environmental impact.

 50 Dominique Hassinger

PhD in Biomedical Engineering

Advisor(s): Vince Beachley

Title: PLA and PCL Nanoyarns as a potential new fully resorbable suture for sport medicine applications

Abstract: Non-absorbable or partially absorbable sutures are commonly used in rotator cuff repair (RCR) due to their high strength; however, they may contribute to stress shielding, hindering enthesis regeneration and tissue remodeling. A fully resorbable suture with appropriate mechanical properties could provide a solution. Nanofibers (1–1000 nm in diameter) mimic the extracellular matrix (ECM) and promote cell attachment, making them a promising solution for tissue engineering scaffolds. Electrospinning, a versatile technique for nanofiber fabrication, paired with a custom parallel track system was used to create rolls of aligned nanofiber sheets. Nanofiber sheets were then twisted into nanoyarn to be tested as potential resorbable sutures. Current nanoyarn systems lack alignment control and have limited output capabilities. 

Polylactic acid (PLA) (12.5% w/v) and polycaprolactone (PCL) (16% w/v) nanofibers were electrospun onto a continuous collector and processed into yarns using a custom-built spinner where uptake and twist were controlled. PLA and PCL monofilaments were fabricated via melt extrusion. All materials underwent tensile testing per the US Pharmacopeia (USP) protocol, suture retention testing, strength retention and degradation studies in PBS and lipase over 0, 3, 5, and 7 days.

Aligned, post-drawn PLA and PCL nanoyarns were successfully fabricated. Compared to monofilaments, nanoyarns exhibited greater flexibility but lower strength retention and higher degradation rates. PLA and PCL monofilaments failed suture retention tests as they were too brittle for suturing, while nanoyarns were able to pass through tissue easily and did not cut through tissue or un-tie like the commercial suture. The commercial suture exhibited superior strength retention and lower degradation.

Future studies exploring mechanisms for increased nanoyarn strength, cellular interaction, antimicrobial potential and healed tissue quality will further elucidate the capabilities of nanoyarns as a resorbable suture. 

 51 Zaynab Hazaveh

PhD in Mechanical Engineering

Advisor(s): Behrad Koohbor

Title: Experimental Characterization of Fiber-Matrix Interface Debonding and Transverse Cracking in  Composites

Abstract: The structural integrity of aerospace composites necessitates a multiscale understanding of mechanical failure behaviors at the fiber-matrix interface, where interfacial debonding often precedes transverse cracking and mechanical failure. This study establishes an experimental framework integrating high-resolution Digital Image Correlation (DIC) and Scanning Electron Microscopy (SEM) to characterize fiber-matrix interface debonding in model macro (1 mm diameter) glass and carbon fiber specimens that replicate realistic microstructures. Subjected to transverse loading conditions, the local deformation response at the fiber-matrix interface is initially analyzed through strain and displacement fields developed around macro glass and carbon fiber epoxy composite samples. The study is then extended to double-fiber configurations—glass-glass, carbon-carbon, and hybrid (glass-carbon)—to investigate how inter-fiber spacing and angular orientation influence cracking behavior between the fibers. The experimentally obtained kinematic fields connect global and local deformation responses for glass, carbon, and hybrid cases, revealing key differences in interface strength, crack initiation, and failure progression. Results provide valuable insights into optimizing carbon and glass fiber orientations for lightweight, damage-resistant composites.

52 Matthew Heras

MS in ME

Advisor(s): Behrad Koohbor

Title: Impact Response and Multiscale Deformation in 3D Auxetic Metamaterials

Abstract: Auxetic mechanical metamaterials have attracted interest in impact-mitigating applications. When these structures are subjected to compressive loading conditions, the negative apparent Poisson’s ratio causes them to densify rapidly, thereby activating a self-strengthening mechanism that leads to increased resistance against deformation and damage. The present research will explore the multiscale mechanical and failure response of a specific class of auxetics, referred to as rotating-cell structures. 2D and 3D versions of these structures are fabricated using stereolithography, and are subjected to controlled compressions at quasi-static and low-velocity impact loads. Digital image correlation is used to measure the deformation response of the structures at meso and macro scales. Results obtained in this work indicate that the macroscale impact resistance of the examined structures is strongly dependent on the strain rate sensitivity of their parent material and the thickness of the connecting hinges. These insights are used to design and fabricate modified 2D auxetic structures with gradient hinge thicknesses. The graded structures are shown to outperform their non-graded counterparts in terms of strength and impact-mitigating efficacy. The gradient designs and fabrication methods are shown to be scalable, making them especially applicable to sports and biomechanics research.

53 Md Sadman Islam

PhD in Civil and Environmental Engineering

Advisor(s): Mohammad Jalayer

Title: Analyzing School Bus-Related Crashes in New Jersey Using Machine Learning Techniques

Abstract: Despite various safety initiatives, school bus-related crashes remain a significant concern in the United States. National data from the National Highway Traffic Safety Administration (NHTSA) reveals that from 2007 to 2016, 4% of fatal motor vehicle crashes were school-transportation-related, resulting in 1,282 deaths, including 281 school-age children. In 2018, 117 fatalities and 13,000 injuries were reported due to school bus-related crashes in the U.S., with three fatalities in New Jersey. This issue underscores the urgent need to study the safety of school bus passengers and crashes involving school buses. This paper investigates school bus crashes in New Jersey from 2016 to 2024. Advanced machine learning models, including XGBoost, Random Forest (RF), Support Vector Machine (SVM), Decision Tree and AdaBoost, were employed to evaluate the contributing factors to these crashes. The models were trained and tested to predict crash factors, with their effectiveness assessed based on performance metrics and accuracy. Additionally, SHapley Additive exPlanations (SHAP) analysis was conducted to interpret the impact of various factors on different crash outcomes, such as property damage, injury, and fatality. Our findings provide critical insights into the dynamics of school bus-related crashes and offer data-driven recommendations for enhancing safety measures, contributing to the protection of school children, and informing future safety policies and interventions.

54 Mohamad Keblawi

PhD in Biomedical Engineering

Advisor(s): Vince Beachley

Title: Investigating the Transient Thermal Kinetics of Laser Zone-Drawn PLA Nanofibers

Abstract: One of the main polymers used in biomedical applications is polylactic acid (PLA) based polymers. This is due to its excellent biocompatibility and biodegradability. Many PLA-based polymers have been approved by the FDA for direct contact with biological fluids. Electrospinning has been used to make PLA nanofibers. Post drawing and processing nanofibers has been employed in order to improve the fibers’ mechanical properties and morphology. Laser zone drawing has the potential to process polymer nanofiber with extremely high molecular alignment due to the rapid heating/cooling rates. It utilizes a high power density laser in order to heat a localized fiber zone and mechanically draw it. This localized heating allows for high amounts of drawability as well as fast cooling. Fast cooling leaves little time for molecular chain relaxations. That accompanied with the small diameter has the potential to produce nanofibers with great mechanical strength and high thermal conductivity. This processing technique is not limited to PLA but can be used on other polymers such as PCL, PVDF, etc. For all these reasons, laser zone-drawing can produce nanofibers that can be utilized in many biomedical applications such as biosensor and medical devices. Previous work studied the heating kinetic at steady state fiber temperatures. This study aims to explore the transient heating kinetic of the fiber drawing process.

55 Amine Khelifi

MS in Electrical and Computer Engineering(ECE)

Advisor(s): Nidhal Bouaynaya

Title: Advancing Cockpit Safety: Cost-Effective Flight Data Monitoring with Deep Learning

Abstract: The rotorcraft community faces significantly higher accident rates compared to fixed-wing commercial aircraft, underscoring the critical need for enhanced safety measures. While Helicopter Flight Data Monitoring programs hold promise in improving safety, their widespread adoption remains limited, partly due to challenges associated with the acquisition and analysis of flight data. This paper proposes a Deep Learning (DL) solution to address safety concerns within the rotorcraft community by efficiently acquiring and analyzing flight data for a more automated and comprehensive safety assessment. Specifically, we leverage data obtained with cost-effective off-the-shelf cameras, and process it through Convolutional Neural Networks for automated detection and classification of gauges from several helicopters’ cockpits. Our DL pipeline integrates a classifier for helicopter identification, an object detector for cockpit gauges detection and classification, and a network to infer the reading of each detected gauge. The contribution of this work is two-fold: (1) enhance rotorcraft safety by developing a DL framework capable of detecting, classifying, and inferring gauge readings for different helicopter types, and (2) boost research in the field by constructing a curated dataset valuable for aviation and machine learning communities.

56 Amine Khelifi

MS in Electrical and Computer Engineering (ECE)

Advisor(s): Nidhal Bouaynaya

Title: Advancing Cockpit Safety: Cost-Effective Flight Data Monitoring with Deep Learning

Abstract: The rotorcraft community faces significantly higher accident rates compared to fixed-wing commercial aircraft, underscoring the critical need for enhanced safety measures. While Helicopter Flight Data Monitoring programs hold promise in improving safety, their widespread adoption remains limited, partly due to challenges associated with the acquisition and analysis of flight data. This paper proposes a Deep Learning (DL) solution to address safety concerns within the rotorcraft community by efficiently acquiring and analyzing flight data for a more automated and comprehensive safety assessment. Specifically, we leverage data obtained with cost-effective off-the-shelf cameras, and process it through Convolutional Neural Networks for automated detection and classification of gauges from several helicopters’ cockpits. Our DL pipeline integrates a classifier for helicopter identification, an object detector for cockpit gauges detection and classification, and a network to infer the reading of each detected gauge. The contribution of this work is two-fold: (1) enhance rotorcraft safety by developing a DL framework capable of detecting, classifying, and inferring gauge readings for different helicopter types, and (2) boost research in the field by constructing a curated dataset valuable for aviation and machine learning communities.

57 Muhammad Maaz

MS in Electrical and Computer Engineering

Advisor(s): Nidhal C. Bouaynaya

Title: Efficient ASR Adaptation for Air Traffic Control: Enhancing Aviation Safety with Contextual Error Rate (CER)

Abstract: 

Accurate speech transcription is essential in Air Traffic Control (ATC) to ensure operational safety and efficiency. However, conventional automatic speech recognition (ASR) systems often underperform in ATC settings due to high ambient noise levels and domain-specific phraseology. In this work, we explore advanced fine-tuning techniques for OpenAI’s Whisper ASR model, leveraging Transfer Learning and Low-Rank Adaptation (LoRA) to specialize it for ATC communication. Our models are trained and evaluated on both publicly available ATC benchmark datasets and a large-scale corpus of 500,000 FAA-labeled samples. Beyond traditional metrics like Word Error Rate (WER), we propose a novel Contextual Error Rate (CER) metric that emphasizes the accurate recognition of safety-critical elements such as instructions, altitudes, and call signs. The fine-tuned models demonstrate substantial improvements, reducing WER from over 50% to below 10% in certain scenarios, while significantly enhancing the retention of mission-critical information. By integrating CER, we offer a more context-aware evaluation of ASR reliability in real-world ATC applications. Our approach enhances the safety and effectiveness of automated ATC transcription, supporting real-time decision-making, reducing human workload, and enabling more efficient post-operational safety analysis.

58 Heather Malino

PhD in Engineering Education

Collaborator(s): Ajah, Jamael; Riley, Darby; Malino, Heather

Advisor(s): Cassie Jamison

Title: Exploring the Engineering Classroom Experiences of Students with Non-Apparent Disabilities

Abstract: This work was motivated by prior research that shows that misunderstandings and inadequate accommodations from faculty can exacerbate mental health challenges for these students with non-apparent disabilities (NADs) and that faculty continue to seek better strategies to support them.  This study examines the educational experiences of engineering students with NADs through semi-structured interviews and an inductive thematic analysis. Participants with various NADs, such as physical disabilities, chronic illness, emotional disabilities, and cognitive disabilities, shared how their disabilities shape their classroom experiences. To date, 14 students have participated in interviews and provided feedback. We will present early findings based on data from six participants and our plans for future work. Our research focuses on the external barriers students face in engineering classrooms by addressing three questions: (1) What challenges do students with NADs encounter? (2) What classroom elements contribute to these challenges? (3) What instructor strategies do students find supportive?  Preliminary results reveal that students often struggle to balance their disabilities with the demands of a rigorous course load, disclosure dilemmas, and interpersonal interactions. Themes emerged around their diverse needs for coursework and classroom structure, showcasing both positive and negative experiences with academic practices like group work. Early findings also highlight the traits of supportive instructors, such as proactive communication and signaling openness to accommodations.  Ultimately, this work has found that students actively interpret subtle cues from professors about their willingness to accommodate NADs. Our initial findings advocate for faculty to take intentional, visible steps to foster inclusive learning environments. Our aim is that by illustrating the diversity of student experiences, this research can underscore the importance of continued investigation and action to create equitable opportunities for students with NADs in engineering education.

59 SWATHI MALLURU

PhD in Civil and Environmental Engineering

Collaborator(s): Saidi, Ahmed

Advisor(s): Yusuf Mehta

Title: Performance Evaluation of Full-Depth Reclamation and Cold In-Place Recycling Asphalt Mixtures at  Varying Amounts of Bituminous and Cementitious Additives

Abstract: This study aims to review and synthesize current literature pertaining to Full-Depth Reclamation (FDR) and Cold In-Place Recycling (CIR) best practices, standard design and construction procedures, and the field performance of FDR- and CIR-rehabilitated pavements. This study also involved preparing and distributing survey questionnaires to state agencies across the United States and interviewing Subject Matter Experts (SMEs) from states where FDR and/or CIR is widely implemented. Another goal of this study was to evaluate the performance of CIR mixtures prepared using various design recommendations from different states. The collected information was then used to revise and update the current New Jersey Department of Transportation (NJDOT) specification. Results from the literature review, survey questionnaire and performance tests showed that implementing FDR and CIR technologies can offer several benefits including cost savings (ranging between $10,000 and $50,000 per lane mile), lower gas emissions, and improved pavement performance. Several recommendations were also provided from the survey questionnaire and during the interviews with SMEs to ensure best practices of both FDR and CIR design and construction. These recommendations include the use of cationic slow setting emulsions (CSS-1h), foamed asphalt with performance grade of PG 64 -22 as recycling agents, and Portland cement as chemical additive. Performance testing results validated the recommendations for using Strength and cracking tests such as indirect tensile strength (IDT) and Marshall stability to assess and optimize the performance of both FDR and CIR mixtures.  This study also recommends the use of Asphalt Pavement Analyzer (APA) test for characterizing the rutting performance of FDR and CIR mixtures. The outcomes of the project will serve as a major step towards wider implementation of both FDR and CIR in New Jersey, which will allow NJDOT to become more sustainable and further achieve its goals of being environmentally friendly.

60 Elias Nadi

PhD in Electrical Engineering

Advisor(s): Dr Jie Li

Title: "Optimized Green Hydrogen Production from Offshore Wind turbines: A Smart Control Approach for Sustainable Energy Storage and Grid Integration"

Abstract: The global transition to clean energy is accelerating, with green hydrogen emerging as a key solution for decarbonizing hard-to-abate sectors such as industry, transportation, and residential heating. Challenges related to fossil fuel pollution, rising global temperatures, and the limitations of battery storage highlight the need for sustainable alternatives. Hydrogen, as an energy carrier, offers a promising path forward.

This poster focuses on developing an innovative offshore wind farm system that integrates advanced control strategies to produce and store green hydrogen. The system harnesses offshore wind power to drive electrolysis, splitting water into hydrogen (H₂) and oxygen (O₂). The generated hydrogen is then stored and later converted back into electricity using fuel cells when needed, ensuring a reliable energy supply to the grid. This approach addresses key energy challenges, including wind intermittency, storage limitations, and carbon emissions, by leveraging renewable energy for hydrogen production.

The main contrbution is in the intelligent control algorithms and neural network techniques that dynamically optimize energy distribution among the electrolyzer, Battery Energy Storage Systems (BESS), hydrogen storage, and the grid. These control strategies ensure efficient power allocation, system stability, and maximized hydrogen production, making the system both cost-effective and scalable. By integrating offshore wind power with green hydrogen production and storage, this poster presents a sustainable and resilient solution to modern energy challenges, contributing to the global decarbonization effort.

61 Nicholas Pagliocca

PhD in Engineering; Concentration in Mechanical Engineering

Collaborator(s): Pagliocca, Nicholas; Koohbor, Behrad; Trkov, Mitja

Advisor(s): Mitja Trkov and Behrad Koohbor (equally co-advised by both)

Title: Explainable Data-driven Multiscale Dynamic Models of Soft Robotic Actuators Based on Local Strain Fields

Abstract: Analytical and computational modeling of soft robotic actuators is a formidable challenge for even the most seasoned engineer due to the nonlinear nature of the actuators’ constituent materials and complex multiscale dynamics between the length scales. Even more critical is the compatibility of the model with controls tools to enable useful functionalities in a larger system. We propose using Digital Image Correlation (DIC) to ascertain a set of full-field observables encoding all the length scales of the actuator to be used as the input to system identification algorithms, which provide explainable models of the systems dynamics. An advantage of using DIC over finite element methods in high fidelity modeling is that it enables the practitioner to bypass simulation verification by going directly to experiments. Using flexible structures with rotating squares as the reinforcement for tubular soft actuators as a demonstrating example, we constructed and characterized actuators to collect a set of observables. Using system identification, we constructed an assortment of linear and nonlinear models and assessed their errors, numerical stability, and limitations associated with control. This work provides a general recipe for the rapid data-driven identification of dynamic models for soft robotic actuators from observables encoding multiple length scales.

62 Mitchell Paolello

PhD in Chemical Engineering

Advisor(s): Gerard Capellades

Title: Impurity Incorporation Mechanisms in Pharmaceutical Crystallization Processes

Abstract: Crystallization is a commonly used separation and purification process in the pharmaceutical industry, however most crystallization research focuses primarily on tuning crystal properties in pure systems rather than addressing issues that can occur in crystallization processes, such as the retention of process impurities. Although the presence of impurities above regulatory thresholds has been responsible for pharmaceutical drug recalls, the scientific reasons behind impurity incorporation are not well understood. In this context, a more scientific understanding of how impurities are retained in a drug substance will have implications from both a process engineering and product design perspective. The overall goal of my PhD research has been to study the mechanisms in which impurities incorporate in pharmaceutical crystallization processes with the purpose of expanding both scientific and industrial knowledge critical for manufacturing pharmaceutical drugs with minimal impurities that can be harmful to human and animal patients.

63 Tyler Paupst

PhD in Mechanical Engineering

Advisor(s): Paromita Nath

Title: Multi-Physics Modeling of Polymer-Metal Composites in Material Extrusion Additive Manufacturing

Abstract: The advancement of composite additive manufacturing (AM) has been instrumental in the development of next generation materials and multi-functional structures. While AM technologies began as a rapid prototyping tool, the current state-of-the-art is focused on the adaptation of AM for fabrication of near-net-shape components. In the context of metal additive manufacturing, material extrusion is a promising method for shaping alloys in ambient conditions. Material extrusion additive manufacturing (MEX-AM) leverages the fluidization of metal powder through a polymer binder system to shape metal materials in near-ambient conditions. A robust understanding of the complex polymer binder system is imperative for commercial use of MEX-AM fabricated parts. As experimental methods can be prohibitively expensive, physics-based modeling offers an alternative approach for understanding the process-structure-property relationship of a material class.  This work utilizes a multi-physics computational fluid dynamics simulation to model the thermal and rheologic behavior of pure polymer and polymer-metal composite materials subject to the MEX-AM process. Specifically, the multi-physics model is used to predict the surface temperature and the geometric profile by simulating the deposition of material through extrusion. The deposition of PLA and 17-4 PH stainless steel through MEX-AM is also observed experimentally using a thermal camera during printing and the dimensions of the samples are measured ex-situ with a digital microscope.  The experimental datasets are then leveraged for the validation of thermal and rheologic behaviors of PLA and 17-4PH stainless steel materials predicted by the physics-based model. The current physics-based model effectively simulates the deposition of a single raster, with small errors stemming from material property approximations.

64 Varsha Prahaladan

PhD in Biomedical Engineering

Advisor(s): Vince Beachley

Title: Flow Characteristics of Electrospun Nanofiber Mats: Influence of Fiber Alignment and Density on Fluid Transport

Abstract: Introduction

Electrospinning is a versatile technique used to fabricate nanofibers, which are characterized by their sub-micrometer diameter and high surface-area-to-volume ratio. This technology allows for the controlled manipulation of fiber properties such as diameter, alignment, and density, making it suitable for a broad range of applications including filtration, life sciences, and diagnostics. Specifically, lateral flow assays (LFAs) benefit from nanofiber integration, enhancing sensitivity and specificity due to increased surface area for biomolecule interaction. However, the impact of nanofiber alignment and density on fluid dynamics within LFAs remains underexplored, prompting this study to fill this crucial research gap.

Materials and Methods

This research utilized electrospinning with an Automated Track System to create nanofiber strips from cellulose acetate (CA) and polycaprolactone (PCL) with varied densities and alignments. A 20% w/v solution of CA and an 18% w/v solution of PCL were prepared and electrospun under controlled conditions to produce fibers with horizontal, vertical, and random orientations. These nanofibers were then assembled into strips and tested for fluid flow characteristics using a rhodamine dye solution, enabling the observation and measurement of flow rates through the nanofiber matrices.

Results, Conclusions, and Discussions

The study revealed that fiber alignment significantly influences fluid flow within nanofiber matrices. For CA, horizontal and vertical alignments enhanced fluid dynamics, with vertical alignment facilitating faster flow rates. Conversely, random alignment impeded flow, particularly without paper backing. PCL nanofibers, however, showed negligible fluid movement, underscoring a material-dependent response in fluid transport applications. These findings suggest that manipulating fiber alignment and density can tailor fluid flow in LFAs, potentially improving diagnostic accuracy and efficiency.

This research highlights the potential of nanofiber customization to optimize fluid dynamics in diagnostic applications. By controlling nanofiber properties, LFAs can be designed to meet specific diagnostic needs, enhancing the reaction times and interaction of fluids with reactive agents. Further studies could explore the integration of dynamically responsive materials to improve the sensitivity and specificity of LFAs, extending their applicability in medical diagnostics, environmental monitoring, and food safety.

65 Mohammad Rostami

PhD in ECE

Advisor(s): Huaxia Wang

Title: In-Context Automatic Modulation Classification: First Step Towards One LLM to Predict Them All

Abstract: Automatic modulation classification (AMC) is critical for efficient spectrum management and robust wireless communications. However, AMC remains challenging due to the complex interplay of signal interference and noise. In this work, we propose an innovative framework that integrates traditional signal processing techniques with large language models (LLMs) to address AMC. Our approach leverages higher-order statistics and cumulant estimation to convert quantitative signal features into structured natural language prompts. By incorporating exemplar contexts into these prompts, our method exploits the LLM's inherent familiarity with classical signal processing, enabling effective one-shot classification without additional training or preprocessing (e.g., denoising). Experimental evaluations on synthetically generated datasets—spanning both noiseless and noisy conditions—demonstrate that our framework achieves competitive performance across diverse modulation schemes and signal-to-noise ratios. Moreover, our approach paves the way for foundation models in wireless communications that are robust across varying channel conditions, significantly reducing the expense associated with developing channel-specific models. Overall, this work lays the foundation for scalable, interpretable, and versatile signal classification systems in next-generation wireless networks.

66 Ahmed Saidi

PhD in Civil Engineering

Advisor(s): Yusuf Mehta

Title: Design and Construction of Electrically Conductive Asphalt Pavements in New Jersey and Alaska

Abstract: The demand for sustainable infrastructure in cold regions has prompted the exploration of innovative solutions to address the challenges posed by extreme climates. One of the emerging solutions consists of constructing electrically conductive asphalt (ECA) pavements in cold regions to mitigate safety issues associated with snow and ice accumulation and removal. This paper presents lessons learned from construction projects of ECA pavement sections in New Jersey and Alaska. These lessons learned highlight the best design and construction practices of ECA pavements, covering material selection, design of ECA mixes and pavement structures, design of electrical supply systems, installation of steel electrodes, plant production of ECA mixes, as well as quality control and acceptance operations. This paper also provides several recommendations to consider during ECA construction projects, which include using step-down transformers for safety purposes, producing ECA mixes in batch mix plants, and compacting the ECA layer using static asphalt compactors to secure electrodes in place. The findings of this paper can be used as guidelines for highway agencies to not only ensure smoother construction operations, but also the implementation of ECA pavements with higher deicing efficiency and longer service life in cold climate conditions.

67 Abu Bakar Md Siddique

MS in Civil and Environmental Engineering

Collaborator(s): Siddique, Abu Bakar Md; Eleyedath, Abhary

Advisor(s): Mehta, Yusuf

Title: Construction of Full-Depth Porous Asphalt Pavement Sections for High Traffic Volume Roadways- An Accelerated Pavement Test Case Study in New Jersey

Abstract: Porous Asphalt (PA) mixtures are a hot-mix asphalt type with significantly more interconnected air voids than traditional dense-graded mixes. This technology minimizes tire noise, water splash, and spray while improving skid resistance and wet-weather visibility. PA also helps manage stormwater, reduce impervious land, replenish groundwater, and filter water pollutants. Based on a hydrological design, these structures are commonly used in low-traffic roads, shoulder lanes, walkways, parking lots, and bike lanes as a best practice for stormwater management. This study aims to construct and instrument two full-scale PA test sections to sustain high-traffic loading for facilitating accelerated pavement testing by heavy vehicle simulator loading. The seven-layer test strips with 660 mm (26-inch) and  990 mm (39-inch) thicknesses are designed to withstand 1 million and 13 million Equivalent Single-Axle Loads (ESALs). The design will be evaluated based on the number of cycles to failure using accelerated pavement testing and then calibrated based on the field performance. If the applied ESALs corresponding to the failure of these structures are less or significantly higher than the target ESALs, this would indicate that the structures are either under-designed or over-designed. The design will be fine-tuned in this scenario to enable more efficient design without compromising safety. This work outlines quality assurance procedures, lessons learned, and challenges unique to full-depth PA pavement construction for adequately implementing the designed PA pavement. This study will provide guidelines on constructing PA pavements for high-traffic roads, which will be critical in implementing porous pavement on a larger scale.

68 Amit Singh

PhD in Mechanical Engineering

Advisor(s): Dr. WEI XUE

Title: Polymer nanocomposites as high-performance dielectrics

Abstract: High-temperature superconducting (HTS) cables improve energy efficiency and reduce power losses, making them valuable for modern power grids and naval systems. However, they require specialized insulation to perform reliably at cryogenic temperatures. This study explores polymer-based nanocomposites enhanced with silica nanoparticles to improve insulation performance. Results show that a specific formulation offers superior dielectric strength at cryogenic temperatures, making these materials promising for more efficient and reliable power transmission technologies.

69 Vaibhavsingh Varma

PhD in Mechanical Engineering

Collaborator(s): Uygur, Mehmet

Advisor(s): Mitja Trkov

Title: Fall Prevention through Robotic Exoskeleton Intervention

Abstract: Fall related injuries are a major cause of financial burden and reduction in quality of life especially among the growing elderly population. Robotic exoskeletons endowed with fall prevention capabilities can potentially help prevent these injuries by enhancing or assisting human movements and leg repositioning through active actuation to maintain upright balance. To design such human-like assistive control strategies, it is necessary to understand the strategies employed by able bodied humans that help humans recover from falls after perturbations like slips. In this study, we identified recovery patterns using intersegmental coordination of lower limbs (ISC) from biomechanical data pertaining to slip recovery. A novel Euclidian distance metric (EDM) derived from ISC variations and patterns of angular movements of lower limbs show differences between fall and recovery cases with respect to relevant gait events. These observations will help guide the development of human-inspired high-level fall recovery controllers. Additionally, to test the effectiveness of the controller, we designed and characterized a lower limb pneumatically actuated cable driven exoskeleton prototype that can intervene after the detection of a foot slip related fall by manipulating hip and knee movements. The high-level controller will interface with the low-level controller on the robotic exoskeleton to produce movements necessary for recovery from a perturbed state that might lead to a fall if corrective action is not taken. The current wearable exoskeleton design is capable of assisting hip abduction and knee extension after occurrence of a perturbation. Overall, this research contribution aims to enhance assistive technologies for fall prevention.

70 Vaibhavsingh Varma

PhD in Mechanical Engineering

Collaborator(s): Twomey, Pat, Bush, Leslie

Advisor(s): Mitja Trkov

Title: Detection for Dance Movement Patterns using Virtual Colliders for Augmenting Visual Experience

Abstract: Around two decades ago, art was incorporated into the STEM framework creating STEAM, thus recognizing the importance of creativity in education. In addition, in recent years, various technologies have enhanced the experience of artistic performances. Building upon such creativity, we formed a collaborative study between dancers and engineers at Rowan University, where we visually augmented an improvisational dance performance by having dancers wear expandable and light changing soft actuators. These actuators can move and change lights based on the detected motion and thus visually augment the movements of the dancers. The control algorithm of the actuators is based on a novel approach involving colliders that are virtual mechanical mass-spring-damper elements. The algorithm is based on the dynamics of this virtual system in a respective local reference frames of individual human limbs that is attached to. This has a significant advantage compared to the traditional approaches using global reference frame that suffer signal drift over time. To capture dance movements, dancers wore inertial sensors attached to their body segments. The body position estimates from inertial sensors were derived using the concepts of quaternions and forward kinematics. Colliders are modelled to respond to body movements and a sequence of such responses from different body parts, when surpassing local collider thresholds, were added to a hash chain and compared with pre-defined patterns to predict the type of dance movements. This method also outperforms a fixed threshold-based method to detect movements as the collider moves with the body and always produces an accurate response, whereas a fixed threshold may or may not be crossed due to the inherent variability of movements involved in an improvisational dance performance. Finally, the detected movement was used to cause light changes and corresponding soft actuator motion to enhance the visual experience of the mainstage dance performance.

71 Shahab Edalatian Zakeri

PhD in Biomedical Engineering

Advisor(s): Patrick Hwang

Title: Sildenafil-Releasing Carbohydrate-based Hydrogel for Arteriovenous Fistula Maturation

Abstract: Introduction:

About 500,000 patients in the U.S. suffer from end-stage renal disease, and more than 60% of patients undergo dialysis. Arteriovenous fistulas (AVFs), created by direct anastomosis between a native artery and vein, are considered the gold standard of vascular access for dialysis. However, up to 60% of AVFs fail to mature sufficiently to allow dialysis because of inadequate vasodilation and early venous neointimal hyperplasia development. Therefore, to improve AVF maturation, we have developed a self-assembled carbohydrate-based hydrogel for sustained release of sildenafil, a phosphodiesterase-5 inhibitor, to promote blood vessel dilation and limit smooth muscle cell proliferation. The hydrogel consists of natural guar gum and gelatin polymers which are biodegradable, biocompatible, and FDA-approved. The combination of these polymers allows for tunable gelation properties and drug release kinetics.

Methods:

To improve the mechanical properties of guar gum, we modified it using sodium metaperiodate and produced guar gum with three degrees of oxidation and evaluated with TNBS assay. The sildenafil-encapsulated hydrogel was fabricated using oxidized guar gum, gelatin, and food-grade microbial transglutaminase as the gelatin cross-linker. Gel properties were characterized by rheology and injectability, and the chemical structure was evaluated by XPS and FT-IR.

Results, Conclusions, and Discussions:

Hydrogels were injectable, with those containing higher levels of oxidized guar gum exhibiting a more viscous appearance. Based on rheology tests, increased oxidization level correlated with a higher storage modulus and showed a shear-thinning behavior. Structural evaluation shows Schiff’s base formation between gelatin and oxidized guar gum as well as ester bond formation between oxidized guar gum and citrate salt of

sildenafil. Finally, drug release kinetics test demonstrated sustained release over 1 month. Our results indicate that this hydrogel has great potential to be tested in vivo on rat models of AVF, after performing safety and efficacy studies on vascular smooth muscle cells.

72 Narangerel Gantumur

PhD in BME

Advisor(s): Dr. Ying Chen

Title: 3D-Printed Cardiac Patch with Biomimetic Microchannels for Enhanced Myocardial  Infarction Therapy

Abstract: Myocardial infarction (MI) occurs when blood flow to the heart is blocked, leading to tissue damage and the loss of cardiomyocytes, which severely impairs heart function and requires innovative therapeutic solutions for effective regeneration. Our present research aims to develop a novel, biomimetic cardiac patch for MI therapy. The research creates a new class of resorbable elastomers (Poly(ε-caprolactone)-b-poly(glycerol-co-sebacate-co-alkyne-serinol) block copolyester), with tunable degradation rates, adjustable mechanical properties, enhanced biocompatibility, and photocrosslinkability. These materials are combined with bioactive components, including induced pluripotent stem cells (iPSCs)-derived cardiomyocytes, mesenchymal stem cell (MSC) derived exosomes, and decellularized zebrafish cardiac extracellular matrix (zECM). The project utilizes 3D printing to fabricate a three-layered patch mimicking the heart wall&#39;s structure, with microchannels to guide cell alignment and maturation. Each layer of the patch represents the endocardium, myocardium, and epicardium, with specific cell types and orientations to replicate the natural cardiac tissue architecture. The patch is expected to enhance cell alignment, maturation, tissue regeneration, and improve cell retention and integration, ultimately restoring heart function post-MI. Our approach not only offers a promising solution for heart repair after MI but also suggests a versatile platform for tissue engineering that can be tailored for other organs by altering the ECM source.

73 Liza Guner

PhD in Biomedical Engineering

Advisor(s): Rachel Riley

Title: Engineering Lipid Nanoparticles for Delivery of siRNA in Pediatric Acute Myeloid Leukemia

Abstract: Pediatric acute myeloid leukemia (AML) is the second most prevalent cancer in children. Children diagnosed with this disease are faced with a 70% survival rate and a 25-35% chance of relapse. Current standard-of-care includes chemotherapy and bone marrow transplantations. While these therapies yield desirable results in many patients, some do not respond, their disease becomes resistant to further therapy, or the delivered dose is limited due to severe side effects.  Recently, immunotherapies, such as chimeric antigen receptor (CAR)-T cells, have shown promising results in clinical and pre-clinical testing for treating pediatric AML. However, long manufacturing times, expensive production, and severe adverse toxicities such as cytokine release syndrome, limit the widespread implementation of these therapies. Therefore, there is a need for new therapeutics that are both effective and safer than current options. In this project, we are developing a nanoparticle-based therapy for gene regulation in AML. Towards this goal, we use lipid nanoparticles (LNPs) to deliver therapeutic nucleic acids to specific cells and tissues. LNPs have been tested both pre-clinically and clinically for a range of diseases and for vaccines, and they are FDA approved for several applications. Thus, we have chosen to use LNPs in this project due to their translatability, efficacy, and safety in humans and animal models. We have evaluated a library of LNPs to deliver fluorescently tagged scramble siRNA to pediatric AML cell. We demonstrated that LNPs yield high siRNA delivery to AML cells after 4 hours. From this library, we determined a top-performing LNP and replaced the scramble siRNA with therapeutically relevant β-catenin siRNA. β-catenin is often overexpressed in pediatric AML and causes increased cell proliferation. With this approach, we hypothesize that β-catenin siRNA will silence β-catenin to decrease AML proliferation and survival. Moving forward, we will determine the safety of this LNP platform to deliver β-catenin siRNA. Ultimately, we aim to demonstrate that LNPs can initiate robust gene regulation to halt AML progression and improve survival in patients.

74 Matthias Recktenwald

PhD in Biomedical Engineering

Collaborator(s): Matthias Recktenwald; Hayley Jankowski; Tyler Torres; Sebastián L. Vega

Advisor(s): Vega

Title: Hydrogels Functionalized with N-Cadherin Mimetic Peptides Suppress Unwanted Mesenchymal Stem Cell Differentiation

Abstract: Mesenchymal stem cell (MSC) therapies hold great promise for regenerative medicine due to their multipotency and immunomodulatory properties. However, a key challenge in their clinical application is unintended differentiation during in vitro expansion, driven in large part by the excessive stiffness of standard tissue culture plastic (TCP) substrates. This supraphysiological rigidity activates mechanotransduction pathways, leading to unwanted osteogenic differentiation and limiting MSC therapeutic versatility.

To address this, we engineered hydrogel substrates that are significantly softer than TCP (~10 kPa ) and functionalized them with an N-cadherin-mimicking peptide (HAVDI) to further suppress mechanotransduction pathways responsible for unwanted differentiation. Mechanistically, HAVDI binds cadherin receptors, enhancing Rac1 GTPase activity and promoting cell-cell interactions over cell-matrix signaling. This shift reduces integrin-mediated cytoskeletal tension, suppressing downstream mechanosensitive pathways, including YAP (Yes-associated protein) signaling and Runx2 (runt-related transcription factor 2), both of which drive osteogenic commitment.

To evaluate the impact of mechanotransduction attenuation, we fabricated norbornene-modified hyaluronic acid (HANor) hydrogels functionalized with integrin-binding RGD peptides (for adhesion) and HAVDI peptides (to reduce matrix mechanosensing). Incorporating HAVDI into HANor hydrogels suppressed nuclear translocation of YAP, a key mechanosensitive protein, and Runx2, a bone-specific transcription factor. Importantly, MSCs cultured on these substrates retained their proliferative capacity and expressed stemness markers (CD90, CD73, and CD105), indicating preserved multipotency. 

These findings highlight the potential of HAVDI-functionalized hydrogels to replace rigid TCP for MSC expansion, providing a scalable strategy to produce high-quality MSCs in large numbers while delaying premature differentiation. This innovation could significantly improve cell-based manufacturing processes, advancing regenerative medicine and clinical outcomes.

75 Joshua Yang

PhD in Biomedical Engineering

Advisor(s): Rachel Riley

Title: Novel Ether Ionizable Lipids Complexed into Lipid Nanoparticles Enhance mRNA Delivery Efficiency

Abstract: Lipid Nanoparticles (LNPs) serve as drug delivery platforms for nucleic acids, such as messenger RNA (mRNA), to modulate gene expression. A critical component of LNPs is the ionizable lipid due to their pH-responsiveness - which enables efficient delivery of nucleic acids to cells. Moreover, nucleic acid delivery depends on the ionizable lipid chemical structure, where modification of ionizable lipid structures can significantly influence drug delivery. Here, we synthesized a series of ether-ionizable lipids containing different numbers of ether groups and lipid alkyl-tail lengths. In the series of novel ether-ionizable lipids, we identified top-performing ionizable lipids for mRNA delivery. The novel series of ionizable lipids were delivered to BeWo b30 trophoblast cells - in which the top-performing ionizable lipids achieved greater delivery efficacy. Our initial screening of the top-performing ionizable lipids proposes a relationship between mRNA delivery efficiency on alkyl-tail lengths and the number of ether groups on the polyamine core. When LNPs are formed with these novel ionizable lipids, we observed the leading ionizable lipids had physicochemical characterizations comparable to LNPs formed with benchmark ionizable lipids such as C12-200 and the Moderna SM-102. Our results demonstrate that the novel ether-ionizable lipids can be complexed into lipid nanoparticles to enhance mRNA delivery efficiency.

76 Rachel Young

PhD in Biomedical Engineering

Advisor(s): Rachel Riley

Title: Harnessing Hypoxia to Enhance Lipid Nanoparticle-Mediated mRNA Delivery for Placental Therapeutics

Abstract: Lipid nanoparticles (LNPs) have gained attention as drug delivery platforms for vaccination against COVID-19 and protein replacement therapies for other diseases. Developing LNPs that can safely deliver nucleic acids to the placenta would enable the treatment of placental dysfunction-related disorders, such as preeclampsia, intrauterine growth restriction, and fetal growth restriction. Placental dysfunction-related disorders affect 10-15% of pregnancies with no curative treatment options other than preterm delivery of the fetus and placenta. Placental dysfunction arises from improper placental development early in pregnancy, leading to restricted blood vessel formation and a hypoxic placental microenvironment. Development of therapeutics for the placenta remains a key challenge due to the complex interactions of the placental tissue environment, with the maternal and fetal circulation. Specifically, the syncytiotrophoblast serves as a multinucleated barrier, that regulates endocytosis and transport of molecules in the placenta. Here, we investigate ionizable lipid nanoparticle (LNP) delivery to trophoblasts under physiologically relevant conditions, including hypoxia and forskolin-induced syncytialization. Using first and third trimester trophoblast cell lines, we found that hypoxia alters trophoblast behavior and hinders syncytiotrophoblast formation in vitro. Despite the changes in trophoblast behavior, we found that hypoxia increases LNP delivery. Furthermore, syncytiotrophoblasts demonstrate increased LNP uptake, particularly under hypoxic conditions. Finally, we show successful delivery of a therapeutic mRNA, placental growth factor (PlGF), to syncytialized trophoblasts in hypoxia, providing a proof-of-concept for LNP-mediated gene therapy. These findings offer new insights into placental-targeted drug delivery and establish a framework for developing LNP therapeutics for preeclampsia and related disorders.

77 Jennifer McGraw

M.A. in Television Studies

Advisor(s): Kim Akass

Title: From Primetime to Screen Time: The Evolution of NFL Media Through Generational Lenses  and the Impact of Television’s Evolution on on Fan Engagement

Abstract: The National Football League (NFL) is more than a professional sports league--it is a cultural

institution that reflects and shapes American identity and culture. This research examines how

the NFL engages younger viewers by balancing traditional broadcasting with second-screen

experiences.. It will explore generational media consumption patterns, representation and

diversity in NFL media, narrative strategies in its programming, technological innovations and

the NFL’s overarching role as a cultural institution.

Studying generational shifts in media consumption will reveal insights into the NFL’s ability

to remain relevant amidst changing entertainment landscapes. The research will explore how

younger generations (Millennials and Gen Z) interact with non-traditional platforms like Netflix,

NFL RedZone, and social media. For older generations (Gen X and Baby Boomers), research

will focus on the role of nostalgia and sustaining engagement.

Examining the impact of social issues and activism on the NFL’s storytelling and marketing

strategies will be crucial for this research because representation reflects the league’s efforts to

adapt to a more socially conscious audience. The research will reveal how gender, race, and

inclusion are portrayed in NFL media and how these depictions reflect or challenge broader

cultural shifts. Further, I’ll explain why the NFL’s more socially conscious shift in the past 10

years has been important to engage younger generations. By examining various NFL programs, I

will highlight the use of storytelling to humanize athletes and how the programs blend

entertainment with sports to appeal to casual viewers, likely to be younger audiences.

Narrative storytelling in their programs fosters emotional connections, broadening the NFL’s

audience beyond hardcore fans and engaging viewers on a deeper level. With the influence of

NFL RedZone’s highlight-driven, fast-paced formats mixed with how the NFL incorporates

social media, we will see how the NFL had an increase in younger audience engagement through

these second-screen strategies in traditional broadcasts. Further, with documentaries like

Quarterback, viewers are introduced to humanization of athletes through this powerful type of

storytelling.

Understanding the role of technology highlights how the NFL adapts to digital consumption

habits, ensuring continued relevance in a fragmented media landscape. This study will assess

how second-screen strategies, such as NFL RedZone and social media, have enhanced

engagement with younger audiences. Understanding these innovations highlights how the league

remains relevant in an era of digital consumption.

The NFL’s role as a cultural institution underscores the importance beyond the realm of

sports. The research will examine how the league mirrors and drives social change, cementing its

influence on American culture. By investigating these interconnected themes, the study will

provide a comprehensive analysis of the NFL’s evolution and its ability to navigate dynamic

intersections of media, technology and culture.

78 Emily Kopchick

Biomedical Engineering

Advisor(s): Ying Chen

Title: Investigating the Impact of Piezoelectric Properties on Cell Alignment, Maturation, and Anti-Thrombosis in Resorbable Metallo-elastomer Vascular Grafts

Abstract: Cardiovascular diseases are the leading cause of death worldwide, highlighting the need for effective treatments. Non-degradable vascular grafts, commonly used in surgeries, often result in complications such as thrombosis, stenosis, and low patency rates, especially in small-diameter vessels. Bioresorbable grafts present a promising alternative by promoting arterial regeneration using the body's own capacities. However, they face challenges like complex fabrication processes, mismatched degradation and tissue regeneration rates, and suboptimal long-term patency and endothelialization. Our current research hypothesizes that adding piezoelectric properties to resorbable vascular grafts can address these issues. Piezoelectric materials generate electrical signals in response to mechanical strain, mimicking the natural electrical environment of blood vessels and promoting cellular activities beneficial for vascular repair and regeneration. Our research aims to understand how piezoelectric stimulation influences cell behavior, enhancing endothelial cell alignment, maturation, and anti-thrombosis properties in resorbable metallo-elastomer vascular grafts. The research focuses on three objectives: 1) Develop a new class of resorbable metallo-elastomers with good biocompatibility, tunable degradation rates, and suitable mechanical properties. 2) Integrate piezoelectric materials with these metallo-elastomers for electrowriting vascular grafts. 3) Investigate the effects of piezoelectric properties on cell alignment, maturation, and anti-thrombosis in these grafts using a rat carotid artery interposition model.

79 Katelyn Martino

PhD in Molecular Cell Biology and Neuroscience

Advisor(s): David Devilbiss

Title: Rescuing Cognitive Function After Repeated Mild Traumatic Brain Injury: The Role of Hepatocyte Growth Factor/cMet Signaling

Abstract: Mild traumatic brain injury (mTBI; or concussion) affects an estimated 3 million Americans each year, representing a significant health concern. Mild TBI can lead to behavioral and cognitive deficits, including impaired working memory, decision-making, and other executive functions. Repeat mTBI is associated with more severe, long-lasting cognitive impairment and brain damage that mimics severe TBI. Dysfunctional working memory is a core component of diminished quality of life and difficulty returning to work and school. Currently, there are no FDA-approved treatment options to improve cognitive deficits following TBI.

The brain hepatocyte growth factor (HGF) and its tyrosine kinase receptor (cMet) system are key mediators of procognitive actions, axonal repair, and other anti-inflammatory and neuronal survival processes. The PLC/PKC pathway has been implicated in improving learning and memory function by potentiating NMDA currents. However, the PI3K/AKT/mTOR, Ras/ERK/MAPK, and STAT3 are additional cMet signaling pathways likely involved in the actions of HGF. Nonetheless, the effects of activating the HGF/cMet receptor signaling in the context of neurological diseases remain unclear.

Dihexa, a brain-penetrant small molecule, is a positive modulator of the HGF/cMet receptor system. Prior research has indicated that dihexa can enhance cognitive function, stimulate neurogenesis, and provide neuroprotection in rodent models. We hypothesize that cMet signaling can improve cognitive impairment and act as a neuroprotectant following repeated mTBI. Additionally, we posit that preferential activation of the PLC/PKC/NMDA and PI3K/AKT/mTOR or Ras/ERK/MAPK after dihexa treatment in mTBI underlies its procognitive and neuroprotective actions. Behavioral pharmacology and neuroanatomical approaches were used to assess performance on the T-Maze test of working memory, markers of axonal integrity, and specific signaling cascades following repetitive mTBI and dihexa treatment in rodents. These findings offer crucial insights into a novel therapeutic strategy for repeated mTBI and support the potential role of dihexa in alleviating cognitive deficits resulting from repeated injuries. 

80 Eleni Papadopoulos

Molecular Cellular Biology and Neuroscience

Advisor(s): Rachel Navarra

Title:  Sex-differences in Risk/Reward Decision Making Following Therapeutic Doses of Methylphenidate and Repetitive Mild Traumatic Brain Injury in Rodents.

Abstract: Mild traumatic brain injury (mTBI) often impairs prefrontal cortex (PFC)-mediated executive decision-making processes that lead to increased risk-taking behaviors. Sustaining repetitive mTBIs (rmTBIs) can worsen and prolong these symptoms. The catecholamine neurotransmitters, dopamine and norepinephrine, modulate neural activity within the PFC and catecholamine dysregulation following TBI is theorized to underly executive dysfunction. The psychostimulant, methylphenidate (MPH), elevates catecholamine levels by blocking reuptake transporters and is often used off-label to treat post-injury symptoms. However, it is unknown how rmTBI-induced disruptions of decision-making processes are affected by chronic MPH treatment. Here, the closed head-controlled cortical impact model was used to induce rmTBI in male and female rodents. Following surgeries, rats (n = 12-13/group) received daily administration of saline or low-dose MPH (0.5 or 2 mg/kg, i.p.) and their preference to make risky decisions involving uncertain risk/reward outcomes was measured using the probabilistic discounting task for 4 weeks post-injury. MPH increased risky choice preference only in injured males for 2 weeks post-injury (p = 0.0095). In contrast, MPH disrupted choice preference only in uninjured females within the first week post-injury (p = 0.0137). Upon completion of testing, Western blotting analysis of catecholamine transporter protein levels within the PFC revealed no experimental differences (p > 0.1979). These results suggest MPH treatment may benefit injured females but exacerbate risky behavior in injured males, albeit these effects were not long lasting. These sex-specific responses advise caution for patients exposed to making choices that involve uncertain risk/reward outcomes when considering MPH to treat post-rmTBI executive dysfunction.

81 Vanessa Pizutelli

PhD in Molecular Cell Biology and Neuroscience

Advisor(s): Dimitri Pestov

Title: Hypoxia Induces Ribosomal RNA Fragmentation Mediated by RNase-L

Abstract: Ischemia/Reperfusion Injury (IRI) is a paradoxical phenomenon that involves an initial restriction of blood flow followed by a sudden restoration of perfusion. This type of injury takes place in conditions such as myocardial infarction, acute kidney disease, and ischemic stroke. Despite efforts to develop therapies that target known IRI pathways, clinical trials have largely been unsuccessful. Therefore investigating alternative mechanisms and biomarkers associated with IRI is imperative. During IRI-induced apoptosis, reactive oxygen species (ROS) inflict damage on proteins, lipids, and nucleic acids, including ribosomal RNA (rRNA), which is vital for ribosome function. Our cell culture studies uncovered distinct rRNA fragmentation patterns under oxidative stress, which differ from those observed in hypoxia/reoxygenation scenarios. This indicates that a unique mechanism is involved in IRI-induced apoptosis. One potential contributor to these rRNA alterations is ribonuclease activity. RNase-L, a ribonuclease associated with innate immunity, is upregulated during low-oxygen states and may be responsible for rRNA cleavage in hypoxia/reoxygenation conditions. Northern blot analysis revealed specific rRNA cleavages in wild-type (WT) A549 cells that were absent in RNase-L knockout (KO) A549 cells. Furthermore, WT cells exhibited significant morphological changes following hypoxia, while KO cells remained indistinguishable from control samples. These findings suggest a link between RNase-L and the unique rRNA cleavages observed during IRI-induced apoptosis. Further investigation into IRI-specific rRNA alterations, including fragmentation patterns and nucleotide modifications, could yield valuable insights into ischemic pathology. If validated, rRNA changes may serve as biomarkers for IRI, which can be used to enhance diagnostic capabilities and guide therapeutic development.

82 Haven Predale

PhD in Neuroscience

Advisor(s): Barry Waterhouse

Title: Distribution of Cerebellar Projecting Locus Coeruleus Neurons and their Dendritic Fields in the Mouse

Abstract: The brainstem nucleus locus coeruleus (LC) projects broadly throughout the brain and spinal cord and is a major source of norepinephrine (NE) release. While many studies have examined the LC-NE system in rats, there have been fewer investigations of LC afferent and efferent connectivity in mouse. Additionally, while we know much about LC organization with respect to sensory and cognitive circuitries and the impact of LC output on their associated behaviors, less is known about LC-NE influences on motor network operations and movement control. To address this question, we used a viral-genetic method to characterize the anatomy of the mouse LC and its dendritic fields with respect to LC-cerebellar projections. In our model LC-NE neurons constitutively express tdtomato, allowing visualization of LC-NE soma, dendrites, and axons. Mouse LC consists of a core of NE-containing soma surrounded by a dense dendritic field extending 60-800µm into the peri-coerulear space. The rostral and caudal ends of LC are tubular in shape whereas the primary cluster of LC-NE cells is lens-shaped along the dorsal-ventral axis. To visualize LC neurons projecting to cerebellum we injected CAV2-CMV-Cre into cerebellar terminal fields causing LC projection neurons to flip from tdtomato to green fluorescent protein. This reveals a dense, bilateral distribution of LC cells that send axons to deep cerebellar nuclei (avg=85-180 cells; 68% ipsi, 32% contra) and anterior or posterior cerebellar cortex (avg=53-80 cells; 60% ipsi, 40% contra). Cerebellar-projecting LC neurons are concentrated rostro-caudally within the intermediate to ventral 2/3 of the nucleus, with only scattered cells identified in the dorsal LC. These results contrast with the more scattered, sparse, and predominantly ipsilateral (95%) distribution of the NE-containing cells that project from LC to primary motor cortex. The dendrites of LC-cerebellum projection neurons extend in all directions from the LC core with a preference for medial and lateral sub-regions of the peri-coerulear space. These results indicate that: 1) a substantial fraction of LC output is directed to the cerebellum, and 2) this output is driven by inputs to lateral and medial sub-regions of the peri-coerulear space as well as perhaps information transmitted via the CSF.

83 Christal Rolling

Molecular and Cell Biology

Advisor(s): James Holaska

Title: Nuclear Envelope Protein Emerin is a Key Regulator of Tumorigenic Characteristics in Invasive Triple-Negative Breast Cancer Cells and Noninvasive MCF-7 Cells

Abstract: Emerin is an inner nuclear membrane protein that maintains nuclear structure and rigidity by binding to nucleoskeletal partners at the nuclear envelope. In breast cancer cells, the size and rigidity of the nucleus is inversely correlated with metastasis. Our lab showed triple-negative breast cancer (TNBC) cells had 50% less emerin protein and smaller, dysmorphic nuclei, resulting in increased cell invasion and tumor formation compared to normal breast cells. When TNBC cells expressing exogenous emerin were injected into a murine breast cancer model, both  primary tumor volume and metastasis were significantly decreased compared to vector-only controls. Thus, we concluded that emerin was a tumor suppressor. We predicted that reducing emerin protein expression in noninvasive cancer cells would drive an invasive phenotype, marked by decreased nuclear area and volume, increased cell migration, and increased cell proliferation. To test our hypothesis, we created stable emerin shRNA knockdown lines in noninvasive MCF7 cells and invasive MDA-231 cells and measured nuclear area and volume, cell migration, and cell proliferation. Emerin reduction by 80% in noninvasive MCF7 cells resulted in a more invasive phenotype. This reduced emerin protein expression caused MCF7 nuclei to become smaller and more malleable, resulting in increased impeded cell migration. Since emerin reduction drives cancer invasion, and emerin expression rescues tumorigenic effects of TNBC cells, which have 50% less emerin, we predict increasing emerin expression will block tumor progression and metastasis in patients. Thus, we tested an approach to deliver emerin mRNA into TNBC cells using lipid nanoparticles (LNPs) due to their low toxicity, as demonstrated by the COVID-19 vaccine. We found that emerin mRNA can be successfully delivered to MDA-231 and MCF7 cells, increasing emerin protein expression. We will continue optimizing LNP delivery to minimize toxicity while maximizing protein expression and stability. The ability of emerin LNPs to rescue tumorigenic effects seen in TNBC cells will also be tested. Collectively, these studies demonstrate that emerin is a key regulator of tumorigenesis and metastasis by acting as a tumor suppressor that will be targeted with emerin LNP delivery to rescue tumor growth and metastasis.

84 Timothy Sloand

PhD in Neuroscience

Collaborator(s): Dunham, Ben

Advisor(s): Elizabeth West

Title: Alzheimer’s disease transgenic rats show altered medial prefrontal cortex neurophysiological signatures to reward predictive cues following a change in expected outcome

Abstract: Deficits in the ability to shift behavior following changes in expected outcome value (i.e., flexible behavior) can have devastating consequences for one’s decision-making. Cognitive deficits, including deficits in flexible behavior, often precede the accumulation of canonical neuropathological markers (Aβ plaques and tauopathy) and severe dementia in Alzheimer’s disease (AD) patients. The Tg-F344-AD rat model exhibits age-dependent AD pathology that closely recapitulates human AD progression. AD rats show deficits in flexible behavior—dependent on medial prefrontal cortex (mPFC) encoding—by 6 months of age. Here, mPFC neuronal activity was recorded during an outcome devaluation task to investigate if AD rats show aberrant behavioral responding and/or mPFC neural activity during outcome devaluation. 6-month-old AD rats (n=17) and wild-type littermates (n=17) were presented with two distinct cues as conditioned stimuli (CS+) predicting distinct rewards. A conditioned taste aversion to one reward was induced after which the rats were tested on the same Pavlovian task (under extinction) to evaluate their ability to avoid the CS+ associated with the devalued reward. WT rats spent significantly less time in the food cup during the devalued CS+ (25.8%) compared to the non-devalued CS+ (35.9%). In comparison, AD rats did not differ in the time spent in the food cup during either CS+ (18.6% vs. 19.6%). mPFC electrophysiological recordings revealed distinct neuronal populations that were “phasic” to the CS+ [excited, EXC; inhibited, INH]. Phasic neurons in AD rats were primarily excited to both devalued CS+ (9% INH, 14% EXC) and non-devalued CS+ (10% INH, 15% EXC) while phasic neurons in WT rats were primarily inhibited to both devalued CS+ (13% INH, 11% EXC) and non-devalued CS+ (21% INH, 8% EXC). This hyperactive mPFC encoding of CS+ in AD rats is likely contributing to their impaired flexible behavior.

85 Erin Wannen

PhD in Molecular Cell Biology and Neuroscience

Advisor(s): Jessica Loweth, PhD

Title: Investigating the Role of Ovarian Hormones in Cue-Induced Cocaine Seeking

Abstract: Cues associated with cocaine use are one of the most common relapse triggers, and understanding what promotes cue-induced cocaine craving and relapse is a critical question in the field. Human studies have shown that these measures are impacted by fluctuations in hormone levels, as higher levels of estradiol promote cue-induced cocaine craving in women while higher levels of progesterone reduce craving in both sexes. Enhanced or incubated cue-induced cocaine seeking or craving also changes across the rodent reproductive (estrous) cycle as levels of estradiol and progesterone fluctuate. However, how gonadal hormones impact cocaine craving and relapse vulnerability in both sexes remains unclear. A thorough understanding of the intersection between hormonal and neuronal mechanisms in relapse vulnerability is critical for developing targeted treatment strategies to effectively reduce craving and promote abstinence in individuals with cocaine use disorder. To begin to investigate this, we conducted studies in both intact, naturally cycling and hormonally depleted (ovariectomized) rats. We focused on the basolateral amygdala (BLA), a sexually dimorphic brain region known to play a critical role in cue-induced cocaine seeking. Interestingly, we found an increase in both cue-induced cocaine seeking behavior and BLA excitatory synaptic transmission in females in the estrus stage of the cycle, when ovulation occurs, compared to both females in other cycle stages and males. Our findings indicate that these effects in females are estradiol-dependent. Additional biochemical studies have identified an interaction between cocaine exposure and ovarian hormone fluctuations on BLA glutamate receptor surface expression. Together these studies will significantly advance our understanding of the mechanisms underlying persistent cue-induced cocaine seeking and relapse vulnerability in both sexes.

Funding: Osteopathic Heritage Foundation grant OHFE-F-2022-26 (JL)

86 Emily Hansen

PhD in biomedical sciences

Collaborator(s): Hansen, Emily; Holaska, James M.

Advisor(s): James M. Holaska

Title: Emerin modulates mechanotransduction to facilitate breast cancer metastasis

Abstract: During metastasis, cancer cells traverse the vasculature by squeezing through very small gaps in the endothelium. Thus, nuclei in metastatic cancer cells must become more malleable to move through these gaps. Our lab showed invasive breast cancer cells have 50% less emerin protein resulting in smaller, misshapen nuclei, and higher metastasis rates than non-cancerous controls. Thus, emerin deficiency was predicted to cause increased nuclear compliance, cell migration, and metastasis. We tested this hypothesis by downregulating emerin in noninvasive MCF7 cells and found emerin knockdown causes smaller, dysmorphic nuclei, resulting in increased impeded cell migration. Emerin reduction in invasive breast cancer cells showed similar results. Supporting the clinical relevance of emerin reduction in cancer progression, our analysis of 192 breast cancer patient samples showed emerin expression inversely correlates with cancer invasiveness. 

This data supports that emerin loss is an important driver of invasive transformation and has utility as a biomarker for tumor progression, but how emerin was being downregulated in cancer is still unclear. Therefore, to determine how emerin protein is being altered in such cases, we tested half-lives and the phosphorylation levels of emerin to suggest potential mechanisms for this to occur. Provided that the tumor microenvironment continues to stiffen as tumors progress, we also tested half-lives and phosphorylation in conditions of different extracellular matrix stiffnesses. Our analyses provide key insight into emerin’s role in the progression of breast cancer and metastatic disease.

87 Nicholas Marano

PhD in Molecular Cell Biology and Neuroscience

Advisor(s): James Holaska

Title: Emerin mRNA Lipid Nanoparticles Rescue Myogenic Differentiation of Emerin-Null Myogenic Progenitors

Abstract: X-linked Emery-Dreifuss muscular dystrophy (EDMD1) is caused by mutations in the EMD gene. Emerin is an inner nuclear transmembrane protein that interacts with partners at the nuclear envelope to regulate gene transcription, maintain repressive chromatin architecture, and support nuclear structure. EDMD1 mutations result in loss of emerin expression or emerin function, which cause disruptions in the myogenic differentiation program. Most patients with EDMD1 lack any detectable emerin expression. Differentiation of myogenic progenitor cells lacking emerin exhibit reduced cell cycle withdrawal, reduced expression of myogenic genes, and reduced myotube fusion compared to wildtype progenitors. Global epigenetic histone mark levels were also altered in the absence of emerin, including increases in the transcriptionally active H4K5ac mark and reductions of transcriptionally repressive marks H3K9me2 and H3K27me3. Emerin interacts with HDAC3 which is responsible for the removal of H4K5 acetylation. Emerin also interacts with histone methyltransferases G9a and EZH2 which are responsible for the deposition of methyl groups on H3K9 and H3K27, respectively. Delivery of emerin to emerin-null myogenic progenitors rescues these deficits in myogenic differentiation. Recently, developments in lipid nanoparticle (LNP) technology have shown promise in delivering mRNA constructs to live cells. We hypothesize delivery of emerin LNPs to emerin-null myogenic progenitor cells will rescue impaired myogenic differentiation. We further posit that LNP delivery of emerin to muscle progenitor cells derived from EDMD1 patients can rescue the EDMD phenotype. To begin testing this hypothesis, we generated LNPs containing emerin mRNA. We tested their capacity to infect cells and optimized the conditions (2.5 pg/cell) for expression of functional emerin protein to ensure high-level emerin expression over time. We tested the cytotoxicity of these emerin LNPs and found that higher doses (>30 pg/cell) of emerin LNPs began exhibiting toxicity and inducing cell death. To test functionality, we performed differentiation assays on emerin-null myogenic progenitors dosed with emerin LNPs. We found emerin LNPs rescued differentiation by measuring cell cycle withdrawal, expression of myosin heavy chain, and fusion into myotubes. We also tested for the rescue of epigenetic histone mark (H4K5ac, H3K9me2 and H3K27me3) levels. This analysis is an important foundation for determining whether emerin mRNA LNPs are an effective option for rescuing myogenic differentiation mechanisms in an emerin-null or EDMD1 emerin background.

88 Claire Corbett

PhD in Cell and Molecular Biology

Advisor(s): Elizabeth West

Title: A History of High-Fat Diet Alters Reward Processing and Dopamine Signaling in The Nucleus Accumbens

Abstract: With increased consumption of diets high in fat in modern societies, it is critical to consider the effects of diet on behavior and brain function. Here, we investigated the effects of a high-fat diet on reward processing and dopamine (DA) signaling in the nucleus accumbens (NAc). Male and female Long-Evans rats were divided into a group fed a chow diet (n=16) or a group fed a high-fat diet (n=16) for 12 weeks. At week 10, we measured rats' preference for high-concentration sucrose (12 %) compared to low-concentration sucrose (4 %) for 7 daily sessions and found that rats fed a high-fat diet consumed less of a high sucrose concentration compared to chow rats. Following the preference tests, rats were switch to standard chow and underwent stereotaxic surgery to inject the genetically encoded GPCR-activation-based-DA (GRABDA) and optical ferrules into the NAc. Rats underwent 15 days of Pavlovian conditioning in which one cue predicted a sucrose pellet (CS+) and a different cue did not (CS-) to evaluate learning while measuring NAc dopamine dynamics using fiber photometry. We found that both groups spent more time in the food cup the CS+ (chow: 18.2% ± 2.7; high-fat diet: 12.4% ± 1.4) compared to the CS- (chow: 11.0% ± 2.5; high-fat: 5.9% ± 1.1), indicating intact associative learning. However, behavioral responses to the cues were diminished in rats fed the high-fat diet (i.e., they spent less time in the food cup during both cues) compared to control rats (main effect of diet, p=0.03). Importantly, rats exposed to the high-fat diet exhibited an abolishment of NAc dopamine signaling during reward-predictive cues but intact dopamine dynamics to the reward. Thus, a history of high-fat diet alters reward processing and NAc dopamine signaling.

89 John Tkaczynski

PhD in Molecular Cell Biology and Neuroscience

Advisor(s): Daniel Chandler

Title: Effects of Social Isolation on Locus Coeruleus Opioid Receptor Expression and Affective Behavior

Abstract: Social isolation is a stressor that impairs homeostatic neuroendocrine functions and is associated with the development of several mood disorders characterized by persistent negative affect. Persistent feelings of loneliness have been growing public health concerns for several years and were greatly exacerbated by the onset of the COVID-19 pandemic. The problem has grown so severe the U.S. Surgeon General recently declared loneliness to be an epidemic health concern that is associated with poor mental and somatic health outcomes. Therefore, identifying mechanisms of neuroadaptation that contribute to the development of persistent negative affect is a critical step in the identifying better treatments for mood disorders. One region of the brain that becomes dysregulated in neuropsychiatric disease is the locus coeruleus.  It is innervated by multiple stress-related peptidergic afferents, including those that release endogenous opioids to affect behavior.  It is a major contributor to the behavioral limb of the stress response, but its role in the neurobiology of social behavior is understudied.  Here we show that in laboratory rats, six weeks of social isolation leads to increased anxiety-like behavior, neophobia, reduced sociality, and passive stress coping. These behavioral changes are also associated with downregulation of the δ-opioid receptor and upregulation of the κ-opioid receptor in locus coeruleus.  These findings suggest that extended social isolation promotes dysregulation of several opioid receptor subtypes in a brain structure that has an important role in regulating affective behavior, implicating them as potential targets for the treatment of neuropsychiatric disease associated with social isolation and loneliness.

90 Samantha Bozarth

Research Scholar

Advisor(s): Mark Niedringhaus

Title: Attention, impulsivity, and catecholamine dynamics in a transgenic rat model of Alzheimer’s disease

Abstract: Patients with Alzheimer's disease (AD) often have impaired attention and impulse control, which can be observed prior to classic memory deficits. The prefrontal cortex (PFC) plays a crucial role in executive functioning, and PFC catecholamine levels are critical for regulating attention and impulsivity.  Insufficient or excessive levels of dopamine and norepinephrine impair attentional processing.  Here, 6-month-old transgenic rats (Tg-F344, n=5) developed to recapitulate Alzheimer’s disease pathology and wild-type control rats (n=7) completed a three-choice serial reaction-time task, with simultaneous fiber photometry recording measuring dopamine and norepinephrine signaling in the rat medial prefrontal cortex (mPFC) using GPCR Activation Based Dopamine (GRAB-DA) and Norepinephrine (GRAB-NE). All rats self-initiated a trial, then following a delay, one of three cue lights illuminated on the opposite side of the chamber. The cue duration increased or decreased depending on the rat’s response, where a shorter cue duration increased the attentional burden. A trial was registered as “impulsive” if the response occurred during the delay, “correct” if the rat responded in the illuminated cue, “incorrect” if the rat responded in a non-illuminated cue, and as an “omission” if there was no engagement with any cue within the set duration. Correct trials resulted in the delivery of a food pellet reward, while non-correct trials (impulsive, incorrect or omission) resulted in a 5 s timeout indicated by house light illumination. We found that AD rats had fewer correct pokes (WT: 33.7 +/- 2.8, AD: 25.6 +/- 2.0; p<0.05) and an increased rate of impulsive pokes compared to their wild-type counterparts (WT: 2.3 +/- 0.9, AD: 11.4 +/- 1.4; p<0.05), with no difference in the number of incorrect or omissions.  Changes in catecholamine dynamics will be analyzed as a potential predictor of behavioral outcomes.

91 Christopher Knapp

Postdoctoral Fellow

Advisor(s): Drs. Rachel Navarra and Barry Waterhouse

Title: Effects of repetitive mild traumatic brain injury and methylphenidate treatment on cognitive flexibility in rodents

Abstract: Mild traumatic brain injury (mTBI) often disrupts prefrontal cortex (PFC)-mediated executive functions, such as cognitive flexibility. Cognitive flexibility is the ability to shift behavioral strategies in response to changing environmental demands. While most mTBI symptoms are transient, repetitive injuries can result in more severe and longer lasting cognitive impairments. Cognitive deficits are associated with dysregulation of catecholamines, dopamine and norepinephrine, within the PFC. Methylphenidate (MPH), a psychostimulant that elevates catecholamine levels by blocking their reuptake transporters, has been shown to improve cognitive dysfunction following TBI. Currently, little is known regarding the potential of MPH to alleviate repetitive mTBI-induced deficits in cognitive flexibility. Here, we evaluated the effects of repetitive mTBI on cognitive flexibility and the potential of MPH to facilitate recovery of injury-induced impairments. Rats received a series of 3 closed-head control cortical impact injuries within one week, followed by daily administration of MPH (0 or 2 mg/kg, i.p.) for 4 weeks. Across these 4 weeks post-surgery, rats were evaluated on an automated strategy shifting task, which required them to learn and shift strategies according to changing task demands. Rats initially acquired a visual cue strategy. Twenty-four hours after initial acquisition, rats were assessed for retrieval of the visual cue strategy followed by a series of strategy shifting and reversal learning challenges. Repetitive mTBI increased response times within the strategy shifting test, indicating slower processing speed. Injured animals also demonstrated reduced throughput scores, a performance index that blends accuracy and response speed. Injured animals treated with MPH did not show improved task performance, suggesting the degree of repetitive mTBI-induced impairment to cognitive flexibility may be greater than what can be remedied by this dose of MPH. As such, this model presents a useful approach for evaluating potential treatment strategies for ameliorating the cognitive deficits induced by multiple mTBIs.

92 Rashmi Kulkarni

PhD in molecular cell biology

Advisor(s): Brian Weiser

Title: Evaluating the relevance of Uracil DNA Glycosylase (UNG2) on the efficacy of thymidylate synthase (TS) inhibitors in colon cancer cells

Abstract: Uracil occurs in DNA due to cytosine deamination or through dUTP misincorporation by DNA polymerases. Thymidylate synthase inhibitors such as 5-fluorodeoxyuridine (FDU), pemetrexed, and raltitrexed are known to elevate dUTP levels in the cell, resulting in the accumulation of uracil in DNA and promoting cell death. Uracil DNA Glycosylase (UNG2) excises uracil from genomic DNA to initiate base excision repair pathways. The N-terminal domain of UNG2 has unique binding motifs for interaction with PCNA (proliferating nuclear cell antigen) and RPA (Replication protein A) at the replication fork. We hypothesized that mutations in these binding sites (FF/AA for PCNA) or (NR/DG for RPA) on UNG2 would abolish their interactions, impairing uracil excision activity in cells and increasing sensitivity towards TS inhibitors. Fluorescence anisotropy binding assays confirmed that (FF/AA) and (NR/DG) UNG2 impaired their ability to bind PCNA and RPA, respectively. The (FF/AA) UNG2 variant marginally reversed FDU sensitivity compared to UNG2-KO cells but remained more sensitive than cells expressing wild-type UNG2. Impairment of PCNA binding by UNG2 also caused cells to be hypersensitive to pemetrexed and raltitrexed. RPA binding site mutations on UNG2 also led to hypersensitivity to FDU, Pemetrexed, and Raltitrexed compared to cells expressing wild-type UNG2. Uracil accumulation in genomic DNA using a novel UDGX dot blot was used to evaluate the impact of impaired PCNA and RPA interactions on uracil excision efficiency. While wild-type UNG2-expressing cells displayed minimal uracil accumulation, UNG2-KO and UNG2 variants-expressing cells exhibited significantly elevated uracil levels following FDU and pemetrexed treatment. UNG2-PCNA and UNG2-RPA binding defects led to disrupted co-localization of UNG2 at the replication fork, emphasizing the importance of these interactions in maintaining uracil excision and DNA repair. In conclusion, impaired UNG2-PCNA and UNG2-RPA interactions reduce the efficiency of UNG2’s uracil excision and provide a pharmacological target to augment the efficacy of TS inhibitor drugs.

93 Korie DeBellis

PhD in Geology

Advisor(s): Gerald Rustic

Title: A Multi-Species Approach to Reconstructing Surface and Subsurface Conditions in the Eastern Equatorial Pacific and its Relationship with Surface Variability during the Holocene

Abstract: The El Niño Southern Oscillation (ENSO) is a recurring climate pattern with far-reaching implications for temperature and precipitation patterns across the globe. Ocean conditions in the Eastern Equatorial Pacific (EEP) are closely associated with ENSO conditions. Some researchers postulate that long-term subsurface conditions modulate ENSO variability on decadal to centennial timescales, but the scarcity of high temporal resolution records in marine environments limit our understanding of this relationship. In this study, we utilize microfossils deposited in an EEP deep-sea sedimentary core with a sub-centennial resolution to reconstruct ocean conditions over the last 2,000 years. We measured the Mg/Ca ratios of subsurface foraminifera microfossils – Globorotalia tumida and Neogloboquadrina dutertrei – to develop a detailed reconstruction of subsurface temperatures. Temperatures are obtained using species-specific paleothermometer equations. Our records are compared to existing surface temperature variability records derived from the surface foraminifera Globigerinoides ruber. We find broad agreement between our subsurface reconstructions and ENSO variability upon analysis of our subsurface and surface records. Furthermore, we will use the latest δ¹⁸O measurements of subsurface foraminifera alongside Mg/Ca ratios to reconstruct seawater salinity, an indicator of precipitation trends. These results will enable us to further resolve the relationship between subsurface conditions, surface variability, and ENSO conditions. We hypothesize that trends in precipitation – associated with ENSO conditions – will correspond to changes in subsurface conditions. Lastly, we delve into the implications of conducting paleoceanographic research in a complex subsurface domain, highlighting the benefits of employing a multi-species approach to ENSO and subsurface reconstructions. Our results underscore additional context through which we can enhance our understanding of this ambiguous relationship, which is critical to unraveling the role that ENSO variability plays in a warming world.

94 Vignan Ganji

MS in Urban and Regional Planning

Collaborator(s): He, Qian

Advisor(s): Qian He

Title: Spatial Distribution of EV Infrastructure and Associations with Rent Prices in Washington DC and Philadelphia metropolitan area.

Abstract: This study examines the spatial distribution of electric vehicle (EV) charging stations and their relationship with changes in rent prices across block groups in the Washington, DC metropolitan area and Philadelphia, PA, from 2017 to 2022. We used point data on EV charging stations to aggregate the number of stations within each block group and created a binary variable indicating whether a block group is located within a one-mile buffer of a charging station. We incorporate demographic and housing data from the Census American Community Survey (ACS) and built environment data from the US Environmental Protection Agency (EPA)’s Smart Location Database to control for key contextual factors influencing rent dynamics. 

The research aims to understand whether proximity to EV infrastructure affects housing affordability and whether privately owned EV stations (such as those located in apartment complex garages) are included in the dataset. Demographic indicators include the percentages of Black, Hispanic, and White populations, median household income, and education levels. Housing data consists of the percentage of renter households, median rent prices, and rent affordability. Built environment factors include population density, employment diversity, proximity to transit, and walkability. 

Our preliminary results indicate that areas with greater accessibility to EV charging infrastructure tend to experience rent increases, which were conditioned by both built environment features and demographic characteristics. This analysis highlights the potential for EV infrastructure deployment to shape spatial inequalities in housing costs. The findings of this work underscore the need for equitable planning strategies in urban sustainability initiatives.

95 Shreya Nalla

Masters in urban and regional planning

Advisor(s): Dr. Qian He

Title: Local and State Government led Climate Action Initiatives in the US : Progress and Efficacy

Abstract: As climate change accelerates, local and state governments in the U.S. are assuming an increasingly critical role in shaping the nation’s climate response. With federal action often slow or fragmented in addressing localized and intergovernmental challenges, state and local governments have become key drivers of climate policy, spearheading efforts to reduce greenhouse gas (GHG) emissions, adapt to changing environmental conditions, and build community resilience. This paper examines the effectiveness of these government-led climate initiatives over the past decade, drawing on an extensive review of existing literature (2014–2024). Through an analysis of both successful and less successful case studies, the paper explores key factors such as stakeholder engagement, policy integration, and funding strategies that influence the success of local and state-level climate actions. By evaluating both quantitative and qualitative outcomes, we uncover best practices and identify local governments' critical challenges in translating climate goals into concrete, sustainable outcomes. This assessment will be crucial for informing future policy decisions, as it provides actionable insights for urban planners, geographers, and policymakers. By highlighting the importance of collaboration, adaptive strategies, and a systems-thinking approach, the findings will contribute to more effective and equitable climate action in building resilient communities, mitigating the impacts of climate change, and promoting long-term sustainability.

96 Megan Ngo

PhD in Geology

Advisor(s): Gerald Rustic

Title: Central tropical Pacific thermocline reconstructions from marine microfossils during the Last Glacial Maximum

Abstract: The mean ocean conditions during the Last Glacial Maximum (LGM) are an ideal target for investigating how varying climate forcings relate to climate variability, including the El Niño Southern Oscillation (ENSO). While precessional forcing during the LGM was similar to modern times, the background conditions of ice volume and average global temperatures were different. Paleoclimate reconstructions of the LGM can provide insight into the relationship between background climate conditions and climate variability, including the role that the tropical Pacific thermocline may play in tropical dynamics and ENSO. We investigate the structure and evolution of the central equatorial Pacific thermocline during the LGM using trace element ratios (Mg/Ca) from multiple marine microfossil species of foraminifera. We reconstructed the central equatorial Pacific surface and sub-surface temperatures from Globigerinoides ruber, Neogloboquadrina dutertrei, and Globorotalia tumida foraminifera species during the LGM. We calculate the surface to subsurface temperature gradient in the central tropical Pacific, which shows variations in the thermal gradient, especially at 21–22 ky. These results suggest a possible depth migration of N. dutertrei which, combined with data from G. tumida, may reflect changes in primary productivity or the location of the deep chlorophyll maximum zone. Small observed differences in G. ruber may also indicate changes in the upper water column during the middle LGM. Overall, the vertical thermal structure of the central tropical Pacific varied from 21–22 ky. Our results provide important sub-surface and upper water column data through the LGM, which is valuable in the context of understanding the variability of the central tropical Pacific.

97 Jose de Jesus Argueta Donohue

Post-Doctoral Fellow

Collaborator(s): Tellez-Jimenez, Olivia; Ramos-Ramirez, Patricia; Tliba, Omar

Advisor(s): Omar Tliba

Title: CDK5 Mediates Glucocorticoid Receptor Phosphorylation at Ser211 in Asthmatic Airway Smooth Muscle Cells: A Potential Mechanism Underlying Glucocorticoid Resistance

Abstract: Rationale: Asthma, a chronic respiratory disease, can lead to severe complications and even death in a subset of patients despite glucocorticoid (GC) treatment. The underlying mechanisms for inadequate or non-response to GC therapy remain complex. A model to explore this complexity involves investigating the role of airway smooth muscle (ASM) cells in asthma. Glucocorticoid receptors (GRs) are nuclear receptors. Upon GC binding, the GC-GR complex translocates to the nucleus to regulate gene transcription. Phosphorylation of GR plays a critical role in modulating its activation and influencing its biological activity. Among the phosphorylation sites on GR, Ser211 has been identified as particularly important for its activity. However, the kinases responsible for GR phosphorylation at Ser211 remain unclear. Given the role of cyclin-dependent kinases (CDKs) in regulating various phosphorylation-dependent processes, we hypothesized that CDKs—particularly CDK5—may regulate GR phosphorylation in ASM cells from asthma patients.

Methods: Human ASM cells were pre-treated with the pan-CDK inhibitor Roscovitine (1, 10, and 20 µM) for 2 hours or transfected with CDK5-specific siRNA. Following these treatments, cells were stimulated with cortisol (1 µg/mL) for 1 hour. GR phosphorylation at Ser211 and total GR expression were quantified using Western blot analysis, while cell viability was assessed via the MTT assay. The spatial interaction between CDK5 and GR was examined using super-resolution microscopy.

Results: Roscovitine treatment significantly reduced GC-induced Ser211 phosphorylation by 40% and 60% at 10 µM and 20 µM concentrations, respectively, without affecting cell viability. CDK5 silencing via siRNA decreased Ser211 phosphorylation by 50%. Additionally, super-resolution microscopy revealed a 10% probability of CDK5-GR interaction in the cytosolic compartment following 2 minutes of cortisol stimulation.

Conclusion: These findings suggest that the CDK family, particularly CDK5, plays a key regulatory role in GR phosphorylation at Ser211 in ASM cells. Targeting CDK-mediated pathways may, therefore, represent a promising therapeutic strategy.

98 Olivia Tellez Jimenez

Research Scholar

Collaborator(s): Argueta, Jesus; Ramos-Ramirez, Patricia; Omar, Tliba

Advisor(s): Omar Tliba

Title: miR-144 Regulates GRβ Expression and Proliferation in Airway Smooth Muscle Cells: Implications for Asthmatic Airway Remodeling

Abstract: RATIONALE: Airway remodeling, a hallmark of asthma pathogenesis, remains unresponsive to current anti-inflammatory therapies. Aberrant proliferation of airway smooth muscle cells (ASMCs) significantly contributes to airway remodeling, yet the molecular mechanisms are not fully understood. The glucocorticoid receptor isoform β (GRβ) is linked to enhanced cell migration, proliferation, and resistance to apoptosis in cancer; however, its role in ASMCs in asthma remains unclear. Given that microRNAs (miRNAs) are critical post-transcriptional regulators, this study explores how specific miRNAs regulate GRβ expression and influence ASMCs behavior following stimulation with EGF or PDGF.

METHODS: Primary ASMCs from both asthma and non-asthma patients were treated with EGF or PDGF (10 ng/mL) at 0.5, 1, 3, 6 and 24 hours. GRβ knockdown was achieved using GRβ-specific siRNA, while miRNA activity was modulated by inhibitors or mimics targeting miR-21, miR-33, and miR-144 delivered with Lipofectamine-RNAiMAX. Cell proliferation was assessed using CyQUANT-assay, and GRβ mRNA levels were quantified by qRT-PCR. Data were analyzed using two-way-ANOVA and Tukey's multiple comparisons test.

RESULTS: EGF or PDGF treatment significantly increased GRβ expression in ASMCs from both asthma and non-asthma patients, peaking at 3 hours (p<0.01). GRβ knockdown significantly decreased EGF and PDGF-induced cell proliferation by 16% at 24 hours. Inhibition of miR-21 reduced GRβ expression in untreated and EGF-treated cells, observed exclusively in non-asthma-derived cells (p<0.001). In contrast, miR-144 inhibition reduced GRβ expression in both asthma and non-asthma cells following EGF-treatment. miR-33 inhibition had no significant effect. Moreover, miR-144 inhibition diminished PDGF-induced proliferation in non-asthma ASMCs (p<0.01), whereas treatment with a miR-144 mimic significantly increased GRβ expression and cell proliferation (p<0.001).  

CONCLUSIONS: These findings highlight the role of miR-144 in modulating GRβ expression and ASMC proliferation, suggesting its involvement in airway remodeling in asthma. Further studies are needed to explore miR-144’s mechanistic role and its potential as a therapeutic target.

1. Stephanie Lezotte - CoEd

2. Yolanda Mack - HMRCoE

3. Celeste Del Russo - CCCA

4. Frank Derby - HMRCoE

5. Omar Tliba - Schrieber Vet School

6. Andrea Vernengo - HMRCoE

7. Steve Chin - HMRCoE

8. Renee Demarest - RV-TBES

9. Peter Rattigan - SNHP

10. Cecile Sam - CoEd

11. Susanne Ferrin - HMRCoE

12. Tabbetha Dobbins - SGS

GRAB AND GO LUNCH MOVED TO ROOM G55