Presenter List

Cassava brown streak disease (CBSD) is one of the leading threats to food security in sub-Saharan Africa. It serves as a main source of carbohydrates that can be consumed directly or turned into flour and processed into popular foods like fufu. CBSD is an insidious threat because it mainly affects the cassava roots, with no symptoms on the stem or leaves, making it impossible to detect damage to the crop until harvest. Our goal is to analyze recombination events in CBSD-associated viruses (cassava brown streak virus, CBSV) and (Ugandan cassava brown streak virus, UCBSV) to detect recombination hotspots that could allow us to predict viral evolution and to inform virus resistant breeding efforts. We aligned publicly available genomic sequences from NCBI GenBank, conducted phylogenetic analysis, and detected recombination events with RDP4 software. We detected 31 events in CBSV (all supported P ≤ 1.36x10^-20) and 18 recombination events in UCBSV  (P ≤ 1.081x10^-41). The breakpoints were concentrated in the 3’ end of the genome, appearing mainly in the Nib, Ham1h and CP proteins. Importantly, one recombination event from each virus was due to recombination with an “unknown parent” that BLAST revealed to be a member of the other species – the first documentation of interspecies recombination between these two CBSD-causing viruses. Research on viral recombination is crucial for the understanding of viral evolution, the development of resistant crops and CBSD management techniques that ensures Africa’s economy and food security.

Biography: Keryan A. Astacio-Berríos is a senior Microbiology student at the University of Puerto Rico in Humacao. Initially uncertain about pursuing graduate studies, her passion for science grew throughout her major and experiences. She now enjoys mentoring and tutoring first-generation, low-income students at her home institution. Keryan discovered an interest in research while assisting a graduate student in Dr. Elvia Meléndez-Ackerman’s lab with their thesis on bee species diversity in Puerto Rico’s main urban spaces. This experience motivated her to seek independent research opportunities, leading to her participation in the 2024 RISE cohort. Her project, "Identifying recombination in CBSD-causing viruses," is her first independent research endeavor and computational research experience. Keryan is now enthusiastic about pursuing graduate education in bioinformatics and computational biology.

The Hanford site, located in the state of Washington, is one of the largest nuclear waste sites in the United States containing 56 million gallons of nuclear waste. Currently, vitrification is being used to contain this radioactive waste within borosilicate glass; however, a yellowish salt phase is forming when exceeding the sulfur solubility limit causing corrosion within the melters walls. To avoid the formation of the gall phase, it is imperative to determine the sulfur content inside the glassy matrix. Inductively Coupled Plasma Optical Emission Spectrometry (ICP-OES) is being used to quantify different chemical elements such as sulfur. Unfortunately, there is an incomplete digestion of the glass which leads to erroneous quantification of sulfur. Different combinations of two independent variables, the volume of hydrochloric acid (HCl) and temperature, have been introduced to increase the reaction rates leading to a more thorough digestion process. After running these samples through ICP-OES the combination of 50˚C and 15mL HCl led to a sulfur signal being detected demonstrating 0.48 weight percent sulfur, which is close to the batched sulfur concentration of 0.50 weight %. This improved acid digestion method could now be used to accurately and consistently quantify the different solubility limits within the complex glass matrix of these borosilicate glasses. 

Biography: Thomas Blach is a rising junior at The College of New Jersey pursuing a B.S. in Mechanical Engineering. He is a student-athlete as a part of the cross country and track and field teams. This summer, Thomas conducted research in Dr. Ashutosh Goel’s lab under the mentorship of Nedgine Joseph. His research aimed to improve acid digestion methodologies to quantify sulfur within borosilicate glasses.

Zea mays, commonly known as maize, is an important crop for studying gene regulation, specifically regarding cis-regulatory modules (CRMs)–genomic regions that control gene expression–and transposable elements. Understanding the molecular nature of certain traits allows for their modeling, especially when aiming to increase crop production or quality. In maize, a Hopscotch transposon was previously suggested to regulate the expression of TB1, a domestication gene that represses the growth of tillers (bottom branches) and allows for the proper development of maize ears. This gene is vital to understanding how maize was domesticated from its progenitor, teosinte, and can assist the agricultural industry by optimizing maize growth for human usage. While the region containing Hopscotch was implicated in regulating TB1 expression, it is unclear how and whether other CRMs may also play a role in TB1 regulation. Five CRMs were identified by the lab and collaborators as possible regulators for TB1 due to their chromatin accessibility and the presence of transcription factor binding sites. This study used CRISPR-Cas9-modified generated lines that mutate these CRMs. It characterized them via DNA extraction, Polymerase Chain Reaction, and Gel Electrophoresis to obtain, amplify, and analyze DNA fragments to identify specific deletion alleles. Each mutant allele was then phenotypically analyzed by examining the average number of tillers resulting from each allele and comparing them to wild-type maize. If tillers are present in CRISPR-Cas9-modified maize, it indicates that a specific CRM regulates TB1. We hypothesize that at least one mutation will result in a higher number of tillers and, therefore, contribute to the regulation of TB1 in wild-type maize. Though the importance of CRMs in genomes has been recognized for years, their causes and effects have not been fully studied; this is especially true in plant species with a large genome like maize.

Biography: Kelsie Bouyer is a rising junior at Lafayette College in Easton, PA. She is pursuing a B.S. in Biology and a minor in Theater. At Lafayette, she is the Vice President of her college's theater club, a General Chemistry TA, and a member of an All-Voices A Cappella group. Through RISE, Kelsie was selected to work with the Waksman Institute of Microbiology to study the regulators of the TB1 gene in maize under Dr. Andrea Gallavotti. After graduation, she hopes to obtain a PhD in Biology.

One relatively new way of treating cancer is through the process of protein degradation. This is a natural process in the body that helps deal with unwanted or no longer useful proteins. Usually, cancer comes in the form of tumors which are large growths of usually a single protein being over produced by a cancer cell. In particular, tumors in the brain caused by the overgrowth of alpha-synuclein proteins can be tricky as they can cause other diseases which can hinder them being identified and properly treated due to their location in neural tissue. As such, we seek to design a larger protein capable of marking potential alpha-synuclein that could aggregate for protein degradation. This protein contains two main parts: an E3 ligase and a PDZ domain. E3 ligases are capable of transferring ubiquitin, a common marker for protein degradation, onto the alpha-synuclein. PDZ domains are capable of binding to small molecules such as alpha-synuclein. The E3 ligase and PDZ domain are attached via an alpha-Helicon binding site. Designs for said protein were achieved using deep learning models such as RFdiffusion, ProteinMPNN, and AlphaFold. After a first run of 800 unique designs, results show that fabricating such proteins is possible. Designs maintain desired fold, create desired linker and bundle, and bind in key areas. Filtering using RMSD and interaction energies in key areas will be done to find the best designs. These first designs show potential for testing further with different conditions and proteins discussed above to seek more capable designs. The use of computational modeling will be able to accelerate much of the fabrication of new alpha-synuclein degrading proteins and additionally can help in other areas related to cancer therapies.

Biography: Henry Brandstadter is a rising junior majoring in Physics at Emory University. His research experience in both chemistry and physics has led to him being accepted into RISE, where he is learning about protein chemistry under Dr. Sagar Khare. Henry is a part of the track and field team at Emory and has hobbies such as mountain biking, learning French, and playing board games. Though currently learning Physics, Henry plans on transitioning to Material Science with intentions in the future to complete a Masters in an Engineering field.

Metallopolymers effectively integrate the characteristics of synthetic organic polymers: ease of preparation, processability, and durability – with those of metal complexes exhibiting unique electronic and physical properties (e.g., electrochemical, optoelectronic, magnetic). This synergy allows metallopolymers to be promising targets for the development of new multifunctional conductive materials for various electrochemical contexts (e.g., catalysis, sensors). Most electrochemical applications require systems that can support high current densities to facilitate the desired functions. This motivates the need to structurally, chemically, and electronically characterize metallopolymers in order to optimize conductivity and other properties therein. However, the inherent ambiguity and complexity associated with large polymeric systems pose significant challenges in rationally optimizing parts of these systems to achieve specific functional properties. This is further exacerbated by difficulties conducting solution-phase characterization of metallopolymers (i.e., lack of consistent length, poor solubility). To address these limitations, this project aims to synthesize and characterize truncated model systems for Cr-based metallopolymers to better understand the complex electronic structure of analogous, extended systems. Additionally, these models are expected to exhibit interesting functional properties, such as electrochromism and magnetism, making them of interest for future applications (e.g., data storage, electrochromic windows).

Biography: Joe Bush is a rising senior at Reed College in Portland, Oregon, working towards a B.A. in chemistry. At Reed, Joe conducts inorganic catalysis research with the Bowring group and tutors for organic chemistry. He was selected to participate in the 2024 Advanced Materials REU program at Rutgers University, where he worked under the guidance of Dr. Mark Lipke investigating Cr-based oligomers for the development of functional materials. After graduating, Joe plans to pursue a graduate degree in inorganic chemistry or chemical engineering. Outside of lab, Joe spends his free time playing various sports, discussing his favorite media, and playing trending mobile games. 

This study proposes a novel approach to analyzing continuous positive airway pressure (CPAP) adherence data in patients with obstructive sleep apnea (OSA). While routinely collected, CPAP adherence data remains an underutilized resource in clinical research. We aim to harness this wealth of information to assess circadian rhythmicity in OSA patients, hypothesizing that such analysis will yield critical insights into the modulation of OSA's adverse effects. Our innovative methodology employs a pre-trained convolutional neural network (CNN) for unsupervised clustering of CPAP adherence patterns. By converting adherence data into image format, we have developed a robust clustering method that accurately groups patients based on adherence and chronotype. This approach demonstrates utility in personalizing treatment and evaluating CPAP-induced improvements in OSA symptoms. This research bridges the gap between circadian biology and clinical sleep medicine, potentially advancing personalized interventions for sleep disorders. By offering tailored strategies based on individual circadian patterns, our work aims to significantly impact patient care and outcomes in OSA management.

Biography: Latherial is studying statistics, data science, and computer science at the College of Charleston. He is a dedicated professional specializing in interpretable machine learning and statistical analysis to enhance accuracy and explainability in industry and research. With a strong focus on identifying causations over correlations, he is committed to producing impactful insights. Latherial emphasizes the importance of solid mathematical and statistical foundations in both developing models and ensuring comprehension.

Infertility is on the rise, and one in six women have infertility problems. The single largest cause of infertility in women is a defect in meiosis. Meiosis is unique as it is a two-round cellular divisional process that is specific for the formation of sperm and oocytes. A key step in meiosis is the separation of sister chromatids, with the failure of proper chromosome segregation resulting in infertility or genetic disorders. Understanding how and what is involved in this reproductive system will help researchers understand the causes of infertility in humans and develop potential therapies. To identify the proteins required for infertility in Drosophila, we employed the Gal4/UAS system to assess RNAi knockdowns of selected genes. Genes were targeted for knockdown based on meiotic expression in the ovary (~1200) or having an interesting human homolog with known mutations in infertility patients.  We are using two promoters, nanos and matα, to induce RNAi at different stages of germ cell development. The nanos promoter is active in the premeiotic and early meiotic prophase stages, while the matα promoter is active during meiotic prophase. Female flies with a gene depleted by RNAi were crossed with males carrying a Y chromosome-linked dominant Bar eyes mutation to assess fertility and nondisjunction rates, i.e. the incorrect separation of chromosomes. Nondisjunction was determined by the number of Bar-eyed females (XXY) and wild-type eyed males (XO). Through this screening pipeline, we identified 17 genes associated with high rates of nondisjunction, low fertility, and/or sterility. Future research will focus on identifying the function of these genes through detailed cytological analyses of the ovary. Identifying the tools involved in meiosis will help researchers discover the significance of each gene and understand their role in meiosis and fertility. 

Biography: Kristen Fulford is a rising senior at Commonwealth University of Pennsylvania – Mansfield, majoring in Biology with a concentration in cell and molecular biology. At Mansfield, under the guidance of Dr. Long, she researches how the gut microbiome affects tumor growth and spread. Kristen is a student athlete and dedicated scholar, having made the dean’s list every semester. In addition to being a student athlete, she has gained funding from both the PA and NJ Space Grant Consortiums for her research. This summer, she worked with Dr. Kim McKim in the Waksman Institute, where she screened for meiotic genes in Drosophila. She aspires to pursue a Ph.D. in a biological science that incorporates tissue culturing, molecular, or developmental biology.

With a drastic shortage of fuel stocks around the world, the need to find alternative ways to create long hydrocarbon chains is dire. Standard synthesis of hydrocarbon chains for rubber and fuel utilizes environmentally hazardous techniques. Employing organometallic catalysis through the use of Osmium-centered pincer complexes could effectively create a greener or more cost effective alternative to this standard practice. Synthesizing these metal complexes requires the use of air and moisture free environments, as the main pincer ligand, specifically called “pybox,” for these complexes is air and water sensitive. A glovebox was utilized along with various cannulation techniques to synthesize Pybox Osmium hydride complexes capable of carbon-carbon coupling reactions. Nuclear Magnetic Resonance (NMR) spectroscopy was used throughout all reactions to track the progress of the metalation studies. Due to the electron dense metal center, the peaks of hydrides were shifted more downfield once the bond has been made. Preliminary data has shown that these osmium centered catalysts are capable of carbon-carbon coupling reactions more effectively than previous experiments with iridium-centered catalysts. Novel osmium complexes still need further research to fully understand the implications of differing electron densities. Further development of these complexes in higher yield could potentially bring about a new synthetic pathway to create rubber and fuels, alleviating the stress of these drastic shortages.

Biography: Michael Gallo is a rising senior chemistry major at The College of New Jersey. Interested in environmental protection and public safety, they plan on pursuing a Ph.D. in inorganic chemistry to hopefully one day work for the Environmental Protection Agency conducting organometallic research. Currently they are a part of two research groups at The College of New Jersey working in Dr. Stephanie Sen’s bioorganic lab and Dr. Carolina Borges’ social epidemiology lab acting as the lab coordinator. They are also a member of the National Honors Society of Chemistry, Gamma Sigma Epsilon, acting as the organization’s secretary. Working in the Goldman lab at Rutgers University performing organometallic research has been nothing short of exhilarating, and Michael deeply thanks Alan Goldman and all of his graduate students for creating such a supportive environment. 

Melanoma is the most deadly type of skin cancer, accounting for only 1% of cases each year but over 90% of skin cancer-related deaths. Acral and Mucosal melanoma are rare and highly aggressive forms of melanoma and pose significant diagnostic challenges due to their infrequency and limited understanding. Previous research by Chen Lab in cutaneous melanoma has demonstrated that the ectopic expression of metabotropic glutamate receptor 1 (mGluR1), in melanocytes leads to cell transformation in vitro and tumor formation in vivo. As well as the activation of MAPK and PI3K/AKT signaling pathways. Multiple patient-derived cell lines for both acral and mucosal have been tested and mGluR1 expression was present. Our lab investigated whether mGluR1 activity in acral and mucosal melanoma is similar to previous results obtained in cutaneous melanoma. We took advantage of two known, and previously used, glutamatergic signaling inhibitors: Riluzole and Bay 36-7620 in a commonly used cell viability assay, MTT. Our preliminary results showed that both inhibitors reduced cell survival and growth in acral and mucosal melanoma cell lines in a dose-dependent manner. We then proceed to assess if the mGluR1 receptors are functioning in these acral and mucosal melanoma cells. We exposed the acral or mucosal melanoma cells to mGluR1 specific agonist, quisqualate, using one of the components of MAPK, phosphorylated forms of ERK as readouts for receptor activation. We also preincubate the cells with Bay 36-7620 followed by activation with quisqualate, again, using the phosphorylated ERK as readouts. We detected pERK when the cells were treated with quisqualate and reduced pERK in samples preincubated with Bay-36-7620. These results highlight the modulatory effects of mGluR1 inhibitors on MAPK signaling components. These findings underscore the potential importance of mGluR1 and glutamatergic signaling in the pathogenesis of acral and mucosal melanomas, suggesting avenues for novel therapeutic strategies targeting mGluR1 in treating these challenging cancers.

Biography: Albert Garcia is currently a rising senior at Caldwell University, majoring in Biology. This summer, he dedicated his time to research in the Chen lab, focusing on Glutamatergic Signaling in Acral and Mucosal Melanoma. Albert is passionate about understanding complex biological mechanisms and their implications in medical contexts. Inspired by his research experiences, he aspires to pursue graduate studies and ultimately become a physician. Albert's academic journey at RISE this simmer reflects his commitment to advancing scientific knowledge and contributing to healthcare innovation.

Alpha-synuclein is a protein that regulates synaptic activity; however, missense mutations in this protein can cause it to aggregate in neurons and cause synaptic disfunction which can lead to Parkinson’s Disease, Dementia with Lewy bodies and Alzheimer’s. Alpha-synuclein regulation can lead to treatments for these neurological diseases; therefore, we aim to utilize the ubiquitin-proteasome pathway to degrade alpha-synuclein. E3 ligases are proteins that our bodies use to tag other proteins to be degraded by the proteosome, these ligases have been targets for drug design. To the best of our knowledge there is no methodology to recruit E3 ligases to degrade alpha-synuclein. This type of approach can be revolutionary for alpha-synuclein regulation because many current approaches utilize antibodies, which can be conformation-specific and too large to enter cells. We hypothesize that utilizing computational protein design models we can integrate a helicon that binds an E3 ligase to a protein domain that binds to alpha-synuclein in order to induce protein degradation. The methods include ProteinMPNN to generate sequences for our designed backbone and AlphaFold to predict and verify the sequences designed by ProteinMPNN. Produced designs were scored based on computational estimates of the interaction energies between them and the E3 ligase, as well as the alpha-synuclein, and the program’s confidence on the predicted designs. A total of 6 out of 14,000 designs obtained passing scores. However, the binding between these designs and the ligase was not optimal. More work needs to be done to optimize the passing samples before they can be ready for testing in the laboratory. This new approach can advance the development of new treatments for synucleinopathies and even be applied to a wide range of diseases with minimal modifications. 

Biography: Ian M. García Quiñones is a rising junior from the University of Puerto Rico, Río Piedras campus, completing his B.S. in Biology. His current research at Rutgers University is comprised of protein design based on a computational approach to develop a protein to recruit E3 ligases to degrade Alpha-synuclein. He is interested in molecular biology research with biomedical applications; and plans on pursuing a PhD in cancer biology to continue his studies. 

Immune checkpoint inhibitors (ICIs), including ipilimumab (Yervoy®) and nivolumab (Opdivo®), work by blocking specific immune checkpoint proteins, which are often hijacked by tumor cells to evade immune surveillance. Inhibiting the checkpoint activates lymphocytes to destroy tumors, but results in immune-related adverse events (irAEs) in healthy tissues. To study irAEs in the kidneys and liver, newborn BRGS mice were injected with human stem cells to develop a humanized immune system (HIS) and subsequently implanted with triple negative breast cancer cells. Non-humanized (BRGS) and humanized (HIS-BRGS) mice were treated by vehicle or a combination of ipilimumab and nivolumab (10 mg/kg, weekly, ip) for four weeks. Tumor weights were measured, and kidneys and livers were isolated to determine the concentrations of irAE biomarkers, B Cell Activating Factor (BAFF) and granzyme A, using sandwich-based ELISAs. Compared to non-treated mice, the tumor weight was 50% of decrease in humanized HIS-BRGS mice treated with ipilimumab/nivolumab. Humanizing the immune system significantly increased BAFF and granzyme A protein concentration in the kidneys, but not in the livers. ICI treatment significantly increased granzyme A and BAFF concentrations in the kidneys by 400% and 50%, respectively, while there was no significant effect on concentrations in the liver. These data suggest that lymphocyte proteins are differentially regulated in the liver and kidney toxicity associated with ICIs. As a result, pharmacological targeting of BAFF and granzyme A using inhibitors may reduce the nephrotoxicity, but not the hepatotoxicity, associated with immune checkpoint inhibitor therapy. Supported by R25ES020721, R01CA277313, and Society of Toxicology Intern Program.

Biography: Ashley Gilbert is a chemistry undergraduate student with a pharmacology and toxicology focus. She aims to contribute to the discovery of a way to conduct cancer research without the use of animals while studying treatment and prevention drugs. A major influence in her motivation for pursuing cancer research was her late grandmother, a 3-time cancer survivor.

Tamoxifen is a widely used anticancer drug that has been used to treat hormone-receptor-positive early, locally advanced, and metastatic breast cancers.  Tamoxifen acts as a selective estrogen receptor modulator, hindering the cancer cells’ ability to use estrogen to grow.  While it is a commonly prescribed drug for cancer treatment it has shown to have several issues.  Complications such as acquired resistance and off-target activities which result in side effects such as hot flashes, vaginal dryness, and the development of uterine and endometrial cancer are often seen with Tamoxifen due to its need for improved drug-likeness.  Our research is focused on improving tamoxifen's drug-likeness by introducing isosorbide units to its structure.  We hypothesize that incorporating isosorbide units into tamoxifen can improve the ongoing side effects caused by the drug’s poor solubility, tackle its growing resistance, and decrease the potential for reoccurrence.  Isosorbide is readily available and cost-effective.  It is non-toxic, highly water-soluble (29 mg/ml), and resistant to first-pass metabolism as a scaffold or byproduct, showcasing its potential value in the pharmaceutical industry.  Our lab is interested in leveraging these characteristics to improve the physiochemical properties of tamoxifen.  This research aimed to improve and explore the synthetic approach used to synthesize isosorbide units that would be incorporated into tamoxifen.  An effective pathway to produce isosorbide units would allow for more isosorbide unit derivatives of tamoxifen to be further researched.  

Biography: Rachel Gushikem is a rising senior at Montclair State University where she is majoring in Chemistry. Rachel is involved in on-campus research at her home university focused on the preparation of antimalarial compounds.  In addition to her academic pursuits, Rachel is an active participant in the Louis Stokes Alliances for Minority Participation (LSAMP) program, where she serves as a scholar, peer mentor, and ambassador.  Rachel was selected to participate in the RISE program, where she is conducting research under the guidance of Dr. Spencer Knapp in the Department of Chemistry and Chemical Biology. Her research project aims to improve the synthetic approach to creating isosorbide units, which are intended to enhance the drug-like properties of tamoxifen.  Rachel is passionate about continuing her education and plans to pursue a Ph.D. in Medicinal Chemistry.

40% of patients with triple-negative breast cancer (TNBC) experience recurrence in addition to the disease’s aggressive nature. This study aims to explore targeted cancer therapy by inhibiting the methionine cycle, a process common to all cells but utilized more heavily by cancer cells due to their rapid proliferative nature. Through the enzyme Methionine-adenosyltransferase-2A (MAT2A), methionine is converted to S-adenosylmethionine (SAM), a critical substrate for establishing epigenetic methylation. We will be evaluating the effects of the drug AG-270, a small molecule inhibitor of the MAT2A enzyme, in TNBC cell lines. Inhibiting MAT2A depletes cellular SAM levels, which we hypothesize will disrupt the metastatic capabilities of these cells in a manner previously unexplored in breast cancer models. Our methods will evaluate this using multiple in vitro assays. First, for the scratch assay, a confluent monolayer of the cultured TNBC cell lines will be scraped to create a "scratch." The cells will be divided into two groups: one untreated and the other treated with AG-270 at IC50 concentration. Images will be captured at 0, 24, and 48 hours post-scratch, and the scratch width will be measured at seven points to quantify cell migration. Second, for the colony formation assay, TNBC cells will be seeded and allowed to adhere overnight. They will be divided into the control and treatment group. Cells will be incubated for 10-14 days. Colonies will be fixed, stained, and counted manually to assess the effect of AG-270 on colony formation. Preliminary data indicates that MAT2A inhibition decreases cell migration and colony formation, suggesting a disruption in the metastatic capability of these cells. If AG-270 proves effective, it represents a novel therapeutic strategy that targets the metabolism of TNBC.

Biography: Kelly Herrera Villavicencio is a rising junior at Rutgers University-Newark (RU-N), NJ, pursuing a Bachelor of Arts in Chemistry with a minor in the Honors College. She has consistently earned a place on the Dean’s List every semester since her enrollment. From her first year, Kelly has been actively involved in research, working under Dr. Zhang on DNA nanotechnology. She holds membership in the program Louis Stokes Alliance for Minority Participation and serves as the president of the RU-N chapter. In the summer of 2024, Kelly was selected as a RISE research fellow at Rutgers University-New Brunswick. During this fellowship, she gained valuable experience in cancer biology by working at the Susan Lehman Cullman Laboratory for Cancer Research under the mentorship of Dr. Shams Shams and Dr. McBride. Kelly's ultimate goal is to pursue an MD-PhD in Chemical Biology, aiming to bridge the gap between scientific research and the medical field. Kelly would like to thank her mentors and the RISE program for providing an opportunity that has significantly expanded her knowledge and passion for science.

Spinal cord injury (SCI) is defined by damage to neural circuitry that impairs signals from traveling from the central nervous system to the rest of the body. Previous studies have shown immediate AAV6-Gsx1 gene therapy in neural stem/progenitor cells (NSPCs) promotes neurogenesis, excitatory neuron formation, and improves functional recovery following SCI. Interestingly, these benefits to locomotion begin at 7 days-post-injury (dpi) and persist to 56 dpi. However, the generation of new neurons is not possible within 7 dpi and thus secondary therapeutic effects must be present to drive these early benefits. Single cell RNA sequencing (scRNA-seq) revealed that AAV6-Gsx1 therapy infects not only NSPCs, but also microglia. We hypothesize that microglia engineered Gsx1 activation and promote functional recovery in the acute SCI stage. To investigate this, scRNA-seq was conducted and a supervised clustering analysis was performed on the microglia population to identify 6 distinct populations: interferon producing, migratory, proliferating, lipid processing, inflammatory, and homeostatic. The Gsx1 therapy increased interferon producing and decreased proliferating microglia after acute SCI. Future work will validate these changes using fluorescence in situ hybridization (FISH) before investigation into the mechanism of microglia mediated-functional recovery after acute SCI.

Biography: David Hoyt is a senior at Drew University in New Jersey studying Biochemistry and Molecular Biology with minors in Public Health and Anthropology. At Drew, David has conducted immunology and molecular biology research while also serving as a captain on the Men’s Soccer team for two years. He is also an Action Scholar and Baldwin Honors Scholar and has spent time volunteering outside of Drew for the non-profit organization Fair for Emerging Researchers. Upon completing his bachelor’s degree, David plans on pursuing an MD/PhD to pursue a career bridging the gap between research and medicine.

As Drosophila melanogaster shares a significant number of genes with humans, studying Drosophila can provide insights into sleep regulation, a process that is not well understood. In Drosophila, the insomniac (inc) gene encodes a putative adaptor protein for the Cullin-3 ubiquitin ligase complex. A nonfunctional Inc protein results in fragmented sleep and excess neurons in the mushroom body, a brain region important for sleep. This study intends to determine whether C-terminal Inc mutants can successfully rescue the mushroom body defects caused by a null inc mutation. A prior rescue experiment indicated that transgenic expression of full-length Inc protein rescued sleep in inc mutants to wild-type levels; however, Inc mutants could not rescue sleep. To evaluate if C-terminal Inc mutants could rescue the mushroom body defects of inc mutants, a fly cross was conducted between inc mutants and C-terminal mutants via the GAL4/UAS system. From the resulting progeny, the brains of adult male Drosophila were dissected and visualized through immunohistochemistry and confocal microscopy. Our results suggest that transgenic expression of full-length Inc protein results in a normal mushroom body, but further experimentation is needed to confirm this result. The effects of C-terminal Inc mutants on mushroom body anatomy require further investigation. Studying the function of Inc in Drosophila may ultimately provide insight into how genes shape the development and function of brain circuits that regulate sleep. 

Biography: Judy Jiang is a rising senior at CUNY Hunter College in New York, majoring in Biochemistry. Her research experiences at the NYS Institute for Basic Research and Weill Cornell Medicine sparked her interest in improving detection methods for pediatric disorders and diseases. In the summer of 2024, Judy was selected to participate in the RISE program at Rutgers, where she worked under the mentorship of Dr. Nicholas Stavropoulos to explore how certain genes influence brain circuits that regulate sleep in Drosophila. Although this was a new research area for Judy, her diverse research experiences have continued to solidify her aspiration to pursue a research career and earn a Ph.D.

Cancer metastasis is responsible for 90% of cancer deaths, making it the leading cause of death in cancer patients. Metastatic cancer is usually not found in its early stages due to the lack of reliable imaging methods available, as these tumors may be too small to be caught by the radiologist. Therefore, a highly sensitive imaging solution is needed to detect small tumors. It has been discovered that rare earth doped nanoparticles emit light at short-wave infrared (SWIR) optical wavelengths, beneficial for use as imaging contrast agents. Previous studies have shown that albumin can be used to encapsulate rare-earth doped nanoparticles, making them biocompatible when used in vivo. Ligands of tumor-targeting biomarkers can be attached to the albumin surface to increase imaging specificity. A microfluidic process was developed to improve throughput and efficiency in nanoparticle synthesis. The microfluidic chip allows for uniformity and consistency to allow a controlled environment for synthesis. Although parameters, including flow rates and microfluidic chip design, have already been established, several chemical parameters that are known to influence nanoparticle encapsulation have yet to be explored. This project tests five parameters using a Design of Experiments method to identify the pH, albumin concentration, solvent ratio, NaCl concentration, and rare earth element concentration to optimize nanoparticle size (targeted 100 nm diameter) and brightness (maximum brightness) in microfluidic synthesis. HSA concentration was determined to be a significant factor that affects the yield, and NaCl concentration and solvent ratio has been determined to affect size and brightness. Using these results, this study has helped bring out a new approach to nanoparticle synthesis to optimize parameters for future studies.      

Biography: Hwa-Jin Kwak is a rising senior at the University of Hawaii at Manoa, majoring in Mechanical Engineering and minoring in Pre-Health. She has served on the board for Mortar Board, Pi Tau Sigma, and Keebs at UHM on top of working at a pediatric specialty clinic as a medical assistant. Her hobbies include arts and crafts, going on walks, and spending time with her friends and family. Her research interests are in medical technology in relation to cancer and cancer therapeutics, and she plans to pursue a PhD in Biomedical Engineering. Hwa-Jin would like to thank RISE and the cellular bioengineering REU for their support, as well as Dr. Mark Pierce and Dr. Jay Shah for all their teachings.

As the consumption of plastic continues to rise globally, conventional disposal methods are proving environmentally harmful. Therefore, integrated gasification combined cycle has become a topic of significant interest in the energy sector as it offers a promising approach to converting plastic waste into usable energy, providing an alternative to traditional fossil fuels. In present work, the efficiency and economics of power generation of waste plastic gasification are evaluated and compared to electric power generation from coal and natural gas. An Aspen Plus process simulation was developed to replicate the performance of a GE.7HA gas turbine operating in a combined cycle (GTCC) and a steam injection gas turbine (STIG). The model was used to calculate the electric power generation efficiencies in both GTCC and STIG operating modes. Using a constant heat input of 901 MW_th of either natural gas or syngas derived from the gasification of plastic or coal, the combined cycle achieved efficiencies of approximately 60%, with a total power generation of around 540 MW_e. However, when considering a constant mass input of 5,000 dry tonnes per day of solid fuel, the larger heating value of waste plastic compared to Illinois no. 6 coal resulted in power generation of 979 MW_e for plastic and 666 MW_efor coal. The electric power production efficiency did not vary with scale in the model and remained at approximately 60%. The STIG model achieved efficiencies approximately 6% lower than the combined cycle. While STIG turbines operate with lower overall thermodynamic efficiency compared to GTCC configurations, the lower capital expenditure by omitting the expensive steam turbine unit lowers the installed cost of the plant and can prove attractive for smaller-scale operations such as waste plastic facilities. Overall, this study highlights the competitive performance of waste plastic gasification and provides insights into the efficiencies of different power generation technologies.

Biography: Hiba Laghzizal is a motivated Chemical Engineering senior at California State Polytechnic University Pomona, California. Originally from Morocco, she moved to the United States to pursue higher education. In her free time, she enjoys painting and reading at the beach. Hiba was selected to participate in the 2024 NSF funded Advanced Materials REU, in partnership with the RISE program. She worked under the supervision of Dr. Fuat E Celik, focusing on power generation cycles of plastic waste compared to traditional natural gas and coal. With a special interest in the energy field, Hiba plans to attend graduate school to further her knowledge and contribute to advancements in energy technology and sustainability.

Emily A. Li

Rutgers University - New Brunswick
Co-Authors: Robert Green Warren, Isha Shah, Jonathan P. Singer
Mentors: Dr. Jonathan P. Singer, Mechanical and Aerospace Engineering
Controlling Porosity of Electrosprayed Polyimide Films Through Co-solvent Blending

Polyimide (PI) has been identified as a potential material for lithium-ion battery (LIB) separators due to its hydrophilic behavior, thermal stability, and mechanical strength. PI is applied using electrospray deposition (ESD), which uses high-voltage electric fields to atomize charged droplets from a liquid solution onto a substrate, forming a uniform thin film or coating as the solvent evaporates. However, limited control over pore size, porosity, and morphology of PI-coated separators weakens its competitiveness in charge/discharge capacity and cycle life performance, which are key metrics for LIBs. This study examines the characteristics of 1% PI blended with 1,2-dichloroethane (DCE) and chloroform in a 2:1 ratio, sprayed at four different flow rates (0.3, 0.5, 0.75, and 1 mL/hour) to evaluate the relationship between flow rate and porosity. The PI coatings are deposited directly onto silicon wafers via self-limiting electrospray deposition (SLED). To evaluate porosity, thickness, and morphology of the co-solvent blended sprayed PI films, we utilized scanning electron microscopy (SEM), optical microscopy, and spectroscopic microreflectometry. Porosity measurements for samples sprayed at 0.3 to 1 mL/hour show a nearly 30% decrease in porosity between the lowest and highest flow rates. Additionally, a qualitative assessment of the resulting film morphologies is captured using SEM. Finer control of porosity will allow for more efficient ion transport between the anode and cathode, enhancing the battery’s charge and discharge rates. Further research can explore different co-solvent blends sprayed at lower flow rates to identify additional patterns in porosity.

Biography: Emily "Annie" Li is a rising sophomore undergraduate student at Rutgers University–New Brunswick, pursuing a B.S. in Electrical Engineering. She is also a part of the Engineering Honors Academy at Rutgers University. Emily was selected to participate in the 2024 NSF Advanced Materials REU, in partnership with the RISE program. This summer she is working at the Hybrid Micro/Nanomanufacturing Laboratory (HMNL) at Rutgers Mechanical and Aerospace Engineering, led by Professor Jonathan P. Singer. Her research involves studying the applications of electrospray deposition, a highly sophisticated additive manufacturing technique that is the primary focus of the HMNL lab.

Tropospheric ozone (O₃) levels have been rising recently due to increasing temperatures. This principal pollutant directly impacts air quality and leads to adverse human health effects. O₃ is known to disrupt the alveolar epithelial barrier and initiate inflammatory responses in the lung. O₃ exposure also leads to the formation of reactive oxygen species (ROS), which cause amino acid deficiencies that can be detrimental to cell survival. It is important to understand the biochemical pathways that lead to these effects for new therapeutic targets to be identified. One pathway of interest is the integrated stress response (ISR). This protective pathway is present in eukaryotic cells and becomes active in response to various cellular stressors. A key component of the ISR is the general control nonderepriseble 2 (GCN2); this kinase is a well-known stress sensor that binds to uncharged tRNAs and phosphorylates eukaryotic initiation factor 2 alpha (eIF2a). This activates the ISR, promoting the initiation of programmed cell death (apoptosis) through differential gene transcription and downregulation of protein translation. Our goal is to assess the role of the ISR in alveolar epithelial cell damage caused by inhaled O₃. Wild-type (WT) mice and mice lacking GCN2 (GCN2KO) were exposed to air or O₃ (800 ppb) for 3 hr. Lungs were processed for histological sectioning and protein isolation for immunohistochemistry (IHC) and western blotting, respectively to assess expression of cleaved caspase-3(cl. cas 3), a key enzyme in apoptosis. Our preliminary data from IHC shows an increased expression of cl. cas 3 over the terminal bronchi and alveoli following O₃ exposure in WT mice; loss of GCN2 reduced this response. This suggests a link between the ISR and alveolar epithelial apoptosis after O₃ exposure; these findings may lead to the identification of new pathways to target for treatment of oxidant air pollution-induced lung injury.  Supported by NIH grants ES04738 and ES005022.

Biography: Andrea recently obtained her bachelor’s degree in Environmental Science with a minor in Toxicology from the Interamerican University of Puerto Rico at Aguadilla. Her aspirations to pursue graduate studies motivated her to apply to the RISE/SURF program at Rutgers University, where she had the pleasure of working in Dr. Laskin’s lab on ozone exposure. Her future ambitions are to become an environmental toxicologist, working for either a federal regulatory agency or in the industry. Andrea enjoys cooking, listening to true crime podcasts, and spending time with her family and pets: Pulga, Luna, and Tina.

Antisense oligonucleotides (ASOs) are chemically modified, single-stranded DNA complementary to pre-mRNA and mRNA regions, thereby inhibiting gene expression by hybridizing to these target regions. However, the effective delivery of ASOs poses a significant challenge due to their size and susceptibility to nuclease-induced degradation. We explore the potential use of molecular motors to enhance DNA resistance against nuclease degradation by inducing structural distortion of DNA molecules. Molecular motors are synthetic molecular machines capable of continuous directional rotation, which we expect to utilize to apply force and induce conformational changes when linked to biomolecules. To integrate these approaches, we synthesize a linker molecule based on the molecular motor to crosslink a single-stranded DNA via strain-promoted azide-alkyne cycloaddition. Upon activation with ultraviolet light, the motor distorts DNA, compacting its structure. This distortion restricts nuclease access to flexible DNA regions, enhancing resistance to degradation for optimized delivery of DNA. The light-triggered structural changes of DNA are characterized using high-performance liquid chromatography (HPLC) and gel electrophoresis. Furthermore, we use hybridization studies to examine how the distortion affects duplex formation with complementary DNA strands. By leveraging molecular motors to alter DNA conformation, ASOs achieve more efficient delivery, making them smaller and easier to enter the cell for therapeutic purposes.

Biography: I am a rising senior at The College of New Jersey pursuing a bachelor's degree in chemistry with a specialization in biochemistry. There, my current research in a biophysical chemistry lab, under the guidance of Dr. Bunagan, includes the study of intrinsically disordered proteins and the effect of salt concentration on their secondary structure. Along with my studies, I work in the Chemistry Department’s Front Office as well as being the social media coordinator for the Student Chemists Association. This summer, my research was conducted under Dr. Yuwei Gu and Yuchen Ma and focused on synthetic molecular motors cross-linked to DNA that is used to distort DNA conformation. Upon graduation, I plan on pursuing a Ph.D. in chemistry or biochemistry then entering a career in industry. 

The placenta is a temporary but vital organ that supports fetal growth and development during pregnancy. It is the site of nutrient exchange and fetal growth is dependent on access to these nutrients from the maternal circulation. Due to the high blood flow, placentas are susceptible to damage by xenobiotic particles. Previous studies have indicated an association between fetal growth restriction and exposure to particulates. Sources of exposure include air pollution containing ultrafine particulate matter (<100 nm in diameter). Epidemiological evidence has associated particulate exposure during pregnancy with adverse outcomes. The purpose of this study was to evaluate changes to placental morphology after exposure to particulate matter, which may ultimately affect placental function and fetal development. Sprague Dawley rats were exposed to titanium dioxide aerosols during pregnancy (gestational day 6-19) to mimic exposure to ultrafine particulate matter. Placentas from both male and female fetuses were collected on GD 20, fixed in formalin, and prepared for histological examination using hematoxylin and eosin staining. Zen Blue software was used to measure the area of placental zones and maternal and fetal blood spaces. We observed a significant increase in the size of maternal blood spaces and decrease in the size of the decidua zone in exposed placentas compared to control. This observation was more pronounced in female derived placentas. Understanding how particulate matter exposure affects the placenta will enhance our knowledge of the potential human health outcomes associated with air pollution exposure during pregnancy.

Biography: Destiny McWilliams is a rising senior at Villanova University. She is pursuing a major in Comprehensive Science and minors in Chemistry and Africana Studies. At Villanova, she conducts biochemistry research under Dr. Daniel Kraut. This summer, Destiny has been a part of both the RISE and SURF programs. She worked in the Stapleton Lab where she has been able to confirm her interest in the field of toxicology. After graduation, Destiny hopes to pursue a Ph.D. and work in industry.

As global fossil fuel reserves continue to dwindle, strategies for producing and storing energy from alternative sources are necessary to supplement combustion methods.  Established technologies, such as wind turbines and solar panels, are intermittent and unreliable because of the inability to efficiently store and transport this energy with methods employed today. Thus, the storage of renewably-derived electricity in the form of chemical fuels is an avenue of great interest. To this end, water splitting is a well-studied reaction that generates hydrogen fuel at the cathode and limited-value oxygen gas at the anode in an electrolysis cell.  Current research is exploring the oxidation of alcohol substrates at the anode to generate more valuable chemical products along with hydrogen fuel. The development of a catalyst to facilitate alcohol oxidation for this anode reaction that is capable of being reused without quickly degrading is the target of this research. The goal of this RISE summer research project is to identify and synthesize a more robust catalyst using first-row transition metals.  Thus far, the synthesis of an N-heterocyclic carbene pincer ligand has shown promising results in the steps leading up to iron or cobalt complexation to obtain first catalyst candidates. Future work will explore different substituents on the ligand backbone as well as testing stability of these complexes in an electrocatalytic system to determine an efficient mechanism for electrocatalytic alcohol dehydrogenation.

Biography: Brayden Messinger is a Rising Senior at The College of New Jersey.  He is majoring in Chemistry w/ ACS Research with a specialization in biochemistry.  Since the summer of his sophomore year, Brayden has been doing organometallic chemistry-based research under the tutelage of Dr. Abby O’Connor in the Chemistry department of The College of New Jersey’s School of Science. This past spring, he also participated in an internship at DOW Chemical in Collegeville PA.  He assisted in analytical work in the Volatiles Lab which was manned by Dr. Michelle Gallagher.  Brayden has been a varsity athlete on the football team at The College of New Jersey for the past three years and has a board position on the affiliated Club Volleyball Team.   After graduation, Brayden plans to attend a graduate level PhD program to continue research in organometallic chemistry which he has gained an admiration and passion for through his experiences.

Injury is among the leading causes of death worldwide. For those under the age of 50, injury is second as a cause of death only to infectious disease. Early preventable deaths associated with injury are primarily characterized by uncontrollable hemorrhage while later preventable deaths are primarily attributable to hypercoagulability. Both are progressions of trauma induced coagulopathy (TIC), which has provoked large research interest in the condition and its attenuation. This project saw the creation of a machine learning model that takes data from blood and coagulation-based biomarkers and conducts nonlinear dimensionality reduction on them. These data were gathered on samples from trauma patients before treatment. Our model can, while only inputting these biomarkers, reliably predict patient mortality outcomes. Additionally, we are in the process of scaling the model to also input proteomics data from patients, conduct similar dimensionality reduction, and combine results for a more accurate prediction. The significant result of this project, however, is that our model’s complexity has been lowered to an extent that allows us to conduct weight analysis of all input features. Our analysis has shown that the most important blood biomarkers in determining TIC mortality are clotting rate and levels of fibrinogen in the blood. Our model can be further applied to any metric for testing and ready to provide an importance distribution of all features. These features can then be targeted for specific tests within an ICU for patient stratification, faster treatment, and direct future studies into the biomechanics of selected features.  

Biography: Dylan Miller, a rising sophomore, is pursuing physics at East Carolina University with a research concentration and minor in mathematics. He has been pursuing computational physics research since high school, where his first project considered the influence of characteristic sea state parameters on rogue wave probabilities. At ECU, he is a member of the Hudson lab where his primary focus is developing computational models for analysis of fibrin polymerization in blood clots. He and his mentor, Dr. Nathan Hudson, hope that this research may yield more robust methods of analyzing network strength as well as provide insight to aberrant structure formation. Dylan plans to continue working in research in the Hudson lab until graduation, after which he hopes to pursue graduate studies in physics or biomedical physics.    

Children’s early mathematical skills are foundational for future academic and career success (ten Braak et al., 2022). Although we are all born with an intuitive “number sense” that allows us to process numerical information from birth (Izard et al., 2009), it can only be linked to symbolic numbers via learning, which can be largely impacted by parent-child interactions (Silver & Libertus, 2022). Parents may not be aware of scientific findings regarding the cognitive and neural mechanisms of learning, including the number sense and its supporting brain functions (Wang & Feigenson, 2019). With the inconsistencies in literature of the exact pathways that contribute to the disparities in parents’ beliefs about math (Elliott & Bachman, 2018), parents’ unawareness of scientific findings may contribute by impacting parent-child interactions and, ultimately, children’s math outcomes. We will compare parents’ beliefs and responses to children’s math performance before and after presenting parents with brief and engaging educational materials developed based on research. These materials focus on the innate number sense and its supporting brain structures (Dehaene, 2011). Our pilot data reveals significant changes in parents’ beliefs about the origins of math and malleability of math abilities after engaging with the materials. Moreover, parents showed a stronger tendency to praise their children’s effort rather than raw talent – a tendency that has been shown to have a positive impact on children’s math motivation (Barger et al., 2022). Findings from this study will make important theoretical contributions to understanding the impact of closing the gaps between lay intuitions vs. scientific theories about human cognition, as well as having practical implications for scientific communication and its consequences on education and learning.   

Biography: Roselyn Ortiz is currently a senior at Syracuse University, planning to graduate this coming Fall 2024, and is majoring in Neuroscience and Psychology with a minor in Human Development and Family Sciences. During the academic year, she prides herself in being a mentor for other students, through Syracuse University’s Office of Multicultural Affairs (OMA), and serving the community as part of Alpha Phi Omega, a professional service fraternity, where she is the incoming President for the Fall of 2024. In her free time she enjoys listening to music, playing piano, reading, cycling, and spending time with family and friends. Her research interests include various interdisciplinary topics like parents’ role in children’s mental health and learning, and music and its impact on the brain, especially mental health. She plans to attend graduate school for psychology in the future. She is grateful for the opportunity to conduct research in the Cognition and Learning Center (CALC) Lab this summer under Dr. Jinjing Jenny Wang, in affiliation with Dr. Alex Silver. She would also like to thank the RISE program, the NJSGC, the CALC lab, and the RISE cohort for their support during this journey.

Cystic fibrosis, a genetic disease affecting almost 70,000 individuals worldwide, is characterized by a mutation in the cystic fibrosis transmembrane conductance regulator (CFTR) gene which prompts an overproduction of mucus across organs. In the lungs, a consequence is a decreased rate of mucociliary clearance, leading to the growth of infectious organisms responsible for persistent lung infections. Pseudomonas aeruginosa, an opportunistic bacterium capable of organizing biofilms as defensive mechanisms, is one of the leading causes of lung infection, affecting over 60% of cystic fibrosis patients. Cationic antimicrobials to treat these infections are typically delivered through nebulization, but inactivating electrostatic interactions with the mucus and biofilm components remain a challenge. To overcome these limitations, we investigated the physical stability and antimicrobial activity of novel polyelectrolyte surfactant nanoparticles. These nanoparticles can self-assemble via electrostatic interactions with cationic antibiotics and penetrate dense biological barriers. We implemented a feasible method for collecting, testing, and comparing in vitro nebulized nanoparticles loaded with either polymyxin B (PB) or tobramycin (TB). We collected sizing data pre- and post-aerosolization to assess stability and performed minimum inhibitory concentration (MIC) assays to evaluate antimicrobial activity. PB-loaded nanoparticles demonstrated a size increase immediately after nebulization followed by a decrease, suggesting re-stabilization over time. These nanoparticles exhibited ~2-fold increased antimicrobial activity compared to the free PB. On the other hand, TB-loaded nanoparticles retained stable size distribution pre- and post-nebulization and exhibited a slight decrease in antimicrobial activity when compared to free TB. Our findings suggest that nebulized drug-loaded nanoparticles may be potential therapeutics to target lung infections in cystic fibrosis patients. 

Biography: Amanda S. Padilla López is a senior student at the University of Puerto Rico Mayagüez majoring in Industrial Microbiology with an expected graduation date of December 2024. She is planning to pursue a biomedical profession and is part of multiple STEM organizations that promote learning opportunities for the youth. She participated in the National Institutes of Health STEP-UP Program in 2021 and has been recognized as an American Heart Association scholar after her participation in the SURE Program and Stanford CVI Program in 2022. With research experience in biomedical engineering, public health, microbiology, and cardiovascular health, she is committed to researching innovations that promote patient-specific approaches and economical solutions. She enjoys sports, reading, and traveling. She is currently part of the NSF Cellular Bioengineering REU where, under the mentorship of Dr. Charles M. Roth and Yariel Varela Soler, she is working with nanoparticles to treat biofilm lung infections in cystic fibrosis patients. She is seeking to expand her research knowledge before graduate school and also inspire those with her similar background to aspire for higher education.

Over 130,000 women were diagnosed with breast cancer in 2021. Moreover, mortality rates for black women are higher than for white women and are believed to be due to skin pigmentation potentially altering cancer treatment efficacy. Photodynamic therapy(PDT) is an existing treatment that administers photosensitizers, followed by a specific wavelength of light, to produce high concentrations of reactive oxygen species(ROS) that cause cancer cell death. PDT alone, however, is limited to specific depths of tissues and is used in conjunction with chemotherapy. Chemotherapy damages healthy tissues in addition to cancer, causing severe adverse side effects. By targeting therapeutics at the cancer site, the dosing of these therapeutics can be minimized, reducing damage to healthy tissues and improving treatment effectiveness. We aim to combine the existing PDT therapy with a novel drug targeting and delivery system. The excess production of ROS from PDT at the tumor will drive the crosslinking of acrylate polymers with one-half of a chemistry click pair. The ROS from PDT will initially damage the tumor and then enable the targeting for a payload. We aim to confirm the compatibility of PDT with our novel system. One crucial step is modeling the effect of skin pigmentations on light transmittance, as light transmittance directly affects ROS generation and our system's efficacy. We hypothesize that darker skin models will lead to lower percentages of light transmittance. Tissue mimic models were made by adding desired concentrations of Intralipid to model light scattering and Nigrosin to model light absorption into agar gels and then exposed to 660 nm light. Increasing concentrations of either component reduces the percentage of light transmitted in the sample. Moving forward, we aim to 1)optimize concentrations of each component in tissue mimics, 2)characterize ROS generation from a photosensitizer, and 3)characterize polymer net formation in tissue mimic models.

Biography: Diana Palade is a rising senior at the West Chester University of Pennsylvania pursuing her bachelor's degree in Biomedical Engineering. At West Chester, she was on the Dean's List (GPA of 3.67 or higher) every semester and received the Lei and Song Li Scholarship for Biomedical Engineering in her freshman year. In addition to her academic success, she is a member and treasurer of her university's competitive equestrian team and the Biomedical Engineering Society. Outside of academics, Diana enjoys playing music by volunteering at her local high school jazz band, graduation band, and musical pit orchestra. Additionally, she enjoys improving her horse-riding skills at her barn in her free time, drawing, and learning new skills. After graduation, she hopes to either work in industry as a biomedical engineer or attend graduate school to obtain her PhD in Biomedical Engineering.

Studies have been conducted to understand the mechanism behind the formation of membraneless organelles, also known as biomolecular condensates. These condensates are formed through liquid-liquid phase separation (LLPS) of intrinsically disordered proteins (IDPs), which play important roles in cellular signaling and regulation. Various intermolecular interactions can drive LLPS, while environmental factors such as salt, pH, temperature, etc. , affect a protein's ability to undergo LLPS. We investigated how salt concentration would influence the phase separation of an artificial IDP, (GRGNSPYS)25, because its phase separation was unexpected due to its high net charge. Its LLPS is driven in part due to the arginine and tyrosine in the sequence promoting cation-pi interactions; these interactions are among the multiple that tend to drive LLPS. Previous studies were conducted in the Schuster lab on GRGNSPYS with lower salt concentrations, and concluded that as salt concentration increased the transition temperature also increased, indicating a higher propensity for LLPS. Hence, we conducted research based on higher salt concentrations and observed the effect salt would have on the ability of GRGNSPYS to phase separate. First, we used microscopy to confirm the ability of GRGNSPYS to phase separate in NaCl concentrations ranging from 150 mM to 3 M, as well as analyzed the droplet sizes using bright-field imaging. Then, we ran turbidity assays using a UV-Vis spectrophotometer on these samples to establish if salt would affect the transition temperature. We observed a trend: as we increased salt concentration, the transition temperature increased as well. With higher salt concentrations, the electrostatic repulsion is weaker, allowing for the cation-pi interactions to drive LLPS. Overall, we were able to accumulate more evidence on how salt concentration affects the ability of GRGNSPYS to phase separate. This insight is beneficial to understand the molecular phenomenon of LLPS, for possible use to engineer biomaterials.

Biography: Samantha Reyes is a rising senior at Saint Elizabeth University in New Jersey majoring in biochemistry. This summer she learned valuable research skills while participating in the Advanced Materials REU. She worked in Dr. Benjamin Schuster’s lab with mentor Xinyi Li and gathered research to better comprehend liquid-liquid phase separation of a cationic artificial intrinsically disordered protein. Samantha would like to acknowledge the Schuster lab for all their support this summer as they gave her a new inspiring outlook on research.

Lipase is a powerful digestive enzyme that degrades lipids. However, lipase readily denatures under non-physiological conditions, such as high temperature and/or in environments of high acidity and basicity. Stable enzymes under such extreme conditions are useful for commercial applications, such as in the production of biofuels. Polymers have emerged as a possible solution to stabilize lipase under these conditions. We hypothesize that by understanding the surface chemistry of lipase, polymers can be designed to stabilize lipase, prior to the protein becoming denatured. Twenty-four copolymers were designed using a machine learning algorithm and synthesized via an automated synthesis. The newly synthesized polymers were hybridized with lipase to form polymer-protein hybrids (PPH). To determine the efficacy of each PPH, they were subjected to heat stressing at 80 ℃ for 1 hour. Then, the retained enzyme activity (REA) was determined by measuring the absorbance over time between native and heat stressed PPH. PPH 24 appeared to show the highest amount of REA. The enzyme, polymer and the PPH were analyzed by dynamic light scattering (DLS) for size and by quartz crystal microbalance with dissipation (QCM-D) to study the polymer-protein interactions. In future studies, the data obtained from these 24 polymers will be used as input into the machine learning algorithm to produce the next generation of copolymers even better suited for lipase stabilization. Small Angle X-Ray Scattering (SAXS) will also be used to gain a deeper understanding of the structure of the polymer-protein hybrid. These findings pave the way for more efficient stabilization of lipase, potentially revolutionizing its application in biofuel production, as well as a road map to stabilize other enzymes.

Biography: David is a rising senior at Ramapo College of New Jersey, where he is pursuing a degree in Biochemistry. As a former funeral director, he has always been fascinated by biological processes, which drives his ambition to pursue a Ph.D. in biochemistry or molecular biology. At his home institution, David's research focuses on discovering novel ligninolytic enzymes in various fungal species. This summer, he has worked under the direction of Dr. Sanjeeva Murthy, studying enzyme stabilization. Outside of academics, David has several passions including film and baseball, and is an avid Pokémon Trading Card game player. 

Spinal cord injuries (SCI) are a growing concern in the medical field. Treatments are costly and take a long time to see improvements. Mouse models are the most commonly used approach to test novel SCI treatments, but the progress can be difficult to monitor over time when changes are made gradually. The Basso Mouse Scale (BMS) is a scientifically-recognized way to analyze and assess locomotion in mice. The scale operates on a detailed movement-based scoring system from 0-9. Use of this scale requires visual observation of the mice’s locomotion, making it a time-consuming process that requires training. This research aims to create a device that can effectively monitor and assess the progress of recovery for SCI-afflicted mice. This device is a wearable, energy-harvesting device that can be attached to the mouse’s back and monitor acceleration and angular velocity. Using a machine-learning approach, an algorithm will extract features from the data obtained from the device to predict the BMS score of the data over a period of time. The features extracted from the data were chosen based on their strong correlation to their respective BMS score. Machine-learning models were tested using the MATLAB classification learner, and the random forest model was determined to be the most accurate at predicting the BMS score from the data features. This device and algorithm will streamline the assessments of SCI treatments in an unbiased, efficient way.

Biography: Sophie Rund is a rising senior at Rose-Hulman Institute of Technology. She is pursuing a bachelor’s degree in Biomedical Engineering with a focus in neuroprosthetics and pre-medicine. This summer she was given the opportunity to work with Principal Investigator Dr. Simiao Niu and Graduate Student Mentor Chi Han. She built a foundation in machine-learning and was able to advance her skills in MATLAB. Sophie would like to thank the NSF (National Science Foundation), RISE program, and the REU Cellular Bioengineering program for the opportunity to do research this summer. 

The possibility to develop sustainable energy material systems is made more feasible by investigating liquid and solid-state electrolytes through charge and energy transport. Battery-operated systems, as we know them, rely heavily on lithium-ion batteries. These liquid batteries have limited life cycles and are unstable at higher potentials, making it difficult to power energy-intensive activities. These activities instead require fuel for energy which significantly contributes to the carbon footprint of our environment. Solid-state electrolytes offer a promising alternative due to their increased ion densities, providing higher thermal and electrical stability. However, the diffusion patterns of ions within solid-state electrolytes remain poorly understood. Solid-state silver-iodide (AgI) batteries can be investigated based on their structure and performance by using the molecular dynamics software LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) and employing the constant potential method (CPM). The constant potential method allows for a more accurate representation of electrochemical systems by maintaining a fixed potential during simulations. This approach is important for studying ion dynamics and charge distribution, revealing how the efficiency of these batteries can be optimized. Charge density calculations confirm an increase in cation diffusion at higher potentials, which means improved charging of the battery. The magnitude of this diffusion directly affects the charge fluctuations on the electrodes at each potential. These charge fluctuations will be quantified by calculating capacitance, providing insights into the energy storage capabilities under varied conditions. With this information we can test different materials for the electrodes, temperatures, and potentials to optimize the life-cycle of the silver-iodide solid-state battery. This study highlights the potential of solid-state batteries in reducing carbon emissions and advancing sustainable energy technology, underscoring the importance of advanced simulation techniques in energy research.

Biography: Karolina Wielowski is a rising senior at TCNJ She is pursuing a bachelor’s degree in Chemistry with a specialization in Biochemistry and a minor in Computational and Mathematical Biology. Karolina began her research journey in her sophomore year, conducting solid-state crystal engineering research under the mentorship of Dr. Heba Aboruhama. The following summer, at TCNJ’s Mentored Undergraduate Summer Experience, Karolina found an interest in the computational field, working with Dr. Baker and conducting molecular dynamics simulations using AMBER (Assisted Model Building with Energy Refinement) software to investigate protein dynamics. Karolina’s continued engagement in this field has led to her collaboration with Dr. Baker and Dr. Magnus Andersson of Sweden’s Umeå University, investigating the biophysical properties of the unique Ena Pili found on the bacterium Bacillus cereus, responsible for many food-poisoning outbreaks. As a first-generation student, Karolina has developed an affinity for mentorship, engaging in the Tri-Alpha First-Generation Honors Society, as well as Gamma Sigma Epsilon and the Student Chemist Association. Serving as School of Science Liaison, Karolina’s goal is to encourage interdisciplinary collaboration among departments. Karolina plans to pursue a Ph.D. in computational chemistry before becoming a professor in chemistry, in hopes of providing the same support she received to first-generation students interested in science.

Large-scale weather disturbances – such as cold fronts – play an important role in midlatitude weather, with impacts on our local climate through heavy rainfall, storms, and other extremes. As datasets grow larger, traditional manual detection of such disturbances becomes time-consuming. Recently, an AI-based approach–the Mask R-CNN algorithm–a deep-learning model developed by Facebook AI Research, incorporates Convolutional Neural Networks (CNNs) to automate feature detection in images. Our focus here involves application of Mask R-CNN to identify synoptic weather activity with a high level of confidence, in order to develop catalogues of synoptic events that can then be related to weather conditions. We implemented  a version of the Mask R-CNN algorithm downloaded from GitHub and trained it on a labeled dataset of annotated images from an National Oceanic and Atmospheric Administration (NOAA) archive of 6 hourly weather charts. This methodology involves data preparation, model training, and validation to ensure performance and accuracy. This helps to provide a scalable solution for large-scale data analytics, which is hard to do by hand given the data size. The findings here suggest that the Mask R-CNN algorithm can accurately identify and segment cold fronts that we expect to impact New Jersey. By developing performance metrics, we optimized our model’s accuracy through result visualization using Python. Through subsequent testing and analysis, we iterated further to reach optimal levels. Integrating AI techniques into weather forecasting enhances our predictive capabilities, as weather is tough to forecast. This offers new insights into climate patterns, and future research can refine the model, leading to more advancements in atmospheric science.

Biography: Kevin Wong is a rising junior undergraduate student at Rutgers University-New Brunswick majoring in Computer Science and is planning to minor in Data Science. This summer he worked under the guidance of his mentors Dr. Benjamin Lintner and Dr. Zhao Zhang to utilize the Mask R-CNN algorithm to classify and extract synoptic features from historical weather maps using Python and data tools.