Dilated Cardiomyopathy (DCM) is a heart disease characterized by the thinning and dilation of the heart's walls, which leads to a decrease in blood pumping ability and can progress to heart failure. Many genetic mutations, primarily in components of the sarcomere, have been implicated in causing DCM. One such mutation is the beta myosin heavy chain mutation E525K. This project aims to understand the molecular mechanism by which E525K leads to disease progression using stem cell-derived cardiomyocytes and a unique multi-level approach to characterizing contractility and cell morphology. Here we show that the E525K mutation can lead to both hyper- and hypocontractility depending on the scale of the analysis. We found that in isolated cells, E525K mutants experienced a 65% decrease in sarcomere shortening and that in engineered heart tissues, the max force produced by tissues with mutant cells was 39% lower than WT tissues. Meanwhile, in isolated myofibrils with the mutation peak force was increased by 45% when stimulated with pCa 4.0 calcium. Morphological analysis showed that mutant cells on average have fewer, smaller, less organized sarcomeres than WT cells. This demonstrates that E525K myosin, though linked to DCM, which is associated with hypocontractility, exhibits both hyper- and hypocontractile effects. Cardiomyopathy affects an estimated 1 in 500 people worldwide and is a major cause of heart failure. Novel pharmacological treatments that activate or inhibit myosin are becoming available; however, cardiomyopathy’s genetic nature complicates treatment. Our findings highlight that the underlying mechanisms causing cardiomyopathy can vary greatly even between patients showing similar disease phenotypes. From a clinical perspective, this complicates what medications should be used, demonstrating that a deeper understanding of the underlying mechanism by which cardiomyopathy-related mutations cause disease is imperative to diagnose and treat patients optimally.

Stiffness measures derived from MR Elastography have shown value in guiding treatment decisions and monitoring effectiveness of therapies for liver disease but it requires extra hardware, longer scan duration and is susceptible to motion and breathing artifacts. Recent studies have revealed a strong linear correlation between water diffusion and tissue stiffness, demonstrating that Diffusion Weighted MRI (DWI) can be used to estimate stiffness values in liver tissue. DWI-derived stiffness values may help evaluate treatment-induced changes in breast cancer but to our knowledge, this has not yet been tested. The purpose of my ongoing study is to calibrate DWI estimates of tissue stiffness for the breast by optimizing DWI parameters (diffusion weightings, or ‘b-values’) and  calibration coefficients (a, b), evaluating the potential of stiffness measures for monitoring response to neoadjuvant chemotherapy (NAC) in breast cancer. We collected baseline and early treatment MRI exams from 25 patients undergoing NAC in this IRB approved study along with their treatment outcomes based on pathologic response post completion of NAC. I evaluated  the stiffness values obtained from different b-value pairs (low b-values: 100/200; high b-values: 800,1500,2000 s/mm²) and calibration coefficients(a,b=-9.7,13.9:-10.8,17.5:-8.8,21.2) and compared it to the invasive breast cancer stiffness values reported in literature. I also evaluated the performance of the optimized parameters to predict treatment response. The optimal b-value pairing (b=200,1500s/mm²) and coefficients a=-9.7,b=13.9 produced stiffness values consistent with literature. Using this approach, the performance for predicting treatment outcomes between responder and non-responder groups was AUC=0.84. These preliminary findings suggest that DWI based virtual elastography could serve as a non-invasive tool to assess tumor stiffness and track treatment efficacy, potentially improving breast cancer management.

Capillary microfluidics capitalize on surface tension effects encoded in microchannel geometry and chemistry to transfer liquids without external instruments - making them a user-friendly technology for point-of-care tests. For most applications, hydrophilic surfaces (contact angle < 90˚) are necessary to induce surface tension driven flow. Currently, vacuum plasma chambers that alter surface chemistry achieve this. Unfortunately, hydrophilic properties made with plasma processing are temporary, costly, and unstable. An inherently stable hydrophilic 3D-printing resin containing polyethylene glycol diacrylate (PEGDA) and acrylic acid (AA) was developed for capillary microfluidics [1]. Similarly, our group has also optimized printing parameters for resins containing PEGDA and Lithium phenyl-2,4,6-trimethylbenzoylphosphinate (LAP) that are inherently porous, hydrophilic, and have applications for development of engineered living materials (ELMs) [2]. Our objective was to optimize and validate 3D printing parameters and geometries for both resins using a range of liquid crystal display (LCD) printers. Our proof-of-concept prints for the PEGDA-AA resin had average contact angle measurements of 42.8 ± 8.77°. Percent differences between designed and printed channel lengths, widths, and depths were 31.5 ± 0.23%, 28.9 ± 3.41%, and 2.40 ± 13.9% respectively. Additionally, we have demonstrated the feasibility of autonomous flow of fluids in the PEGDA-LAP resin with coefficients of variations (CVs) of <5% for microchannels of widths ≥ 137.6 µm. By exploring innovative resins, we increase accessibility and capability for rapid and inexpensive prototyping of microfluidics to be applied to diagnostic tests. These methods reduce costs and carbon footprints relative to traditional additive manufacturing methods.

The effectiveness of a drug candidate depends on its ability to distribute to its target site of action after administration. Thus, a primary concern for drug delivery labs like the Pun lab is preventing drugs from being cleared from the bloodstream by the body's renal system before they are able to accumulate to therapeutic levels at their site of action. In short, one important goal in drug delivery research is to find ways to extend a drug's blood circulation half-life. Conjugating drugs to the large molecular weight molecule polyethylene glycol (PEG) to slow their clearance kinetics is the current gold-standard method, but a crucial drawback is that PEG's large size leads to its potentially toxic buildup in tissues like the liver. To get around this problem, my project aims to develop a drug delivery platform that will allow small molecule drugs to reversibly bind, or in other words "hitchhike" onto human serum albumin (HSA), an abundant protein in blood plasma with an extraordinarily long half-life. At this point in my project, I have successfully synthesized a novel fatty acid monomer with a methacrylate functionality that can be used to copolymerize the monomer with therapeutic small-molecules or peptides to improve their circulation half-life. The next steps will be to copolymerize the fatty acid monomer with pGmMA, a water-soluble polymer, and use biolayer interferometry to test the fatty acid monomer's ability to coordinate to albumin, which will confirm its efficacy as a drug delivery platform. If successful, this project has the potential to provide a generalizable improvement to the pharmacokinetics of various kinds of small-molecule drugs or peptides, enhancing their potency and overall ease of treatment. 

The proximal tubule (PT) and glomerulus are vital blood-filtering components of the nephron, the functional unit of the kidney. The components’ micro-scale sizes and intricate three-dimensional structures are critical to kidney function, although accurate in vitro modeling has proven difficult. Limitations in fabrication techniques have forced size scaling and imprecise morphology in models. In this study, we addressed fabrication limitations using multiphoton ablation to etch intricate, three-dimensional proximal tubule and glomerulus vessels in collagen hydrogels. We sought to demonstrate model viability by introducing human proximal tubular epithelial cells (hPTECs) and human umbilical vein endothelial cells (HUVECs), respectively, through cell perfusion. However, we encountered a significant challenge: due to the small diameter and high curvature of the micro-scale channels, the cells tended to aggregate, disrupting cell profusion and cellularization throughout the vessels. Cell aggregation was especially prominent in the glomerulus model due to the more tortuous and complex geometry. While our cellularization trials on native-scale models proved it is feasible to perfuse cells throughout the vessel, we still need to refine cellular profusion and cellularization. To improve cellular profusion and cellularization, we are first studying a 1.5-scale glomerulus model. The scaled model's increased vessel diameter and lower curvature demote cell aggregation and enhance the ease of cell profusion. We anticipate that cellularizing the 1.5-scale model will provide a deeper understanding of the variables facilitating cell profusion that we can use to improve native-scale vessel cellularization. Fabricating native-scale, accurate in vitro PT and glomerulus models is crucial for developing a deeper understanding of hemodynamic influence on kidney function. These findings contribute to the fabrication of more biomimetic in vitro PT and glomerulus models that will pioneer therapeutics and the understanding of kidney physiology and pathology.

Hypertrophic Cardiomyopathy is the most common form of hereditary heart disease affecting ~1:500 individuals, characterized by progressive thickening of the left ventricular wall. The first mutation linked to this disease was the heterozygous R403Q mutation in human beta-myosin heavy chain (β-MHC). Conflicting reports of contractile kinetics between human myectomy samples vs transgenic mouse and rabbit models motivated us to study the molecular mechanisms of altered contraction in a CRISPR/Cas9 gene edited human inducible pluripotent stem cell line. Following differentiation to cardiomyocytes (hiPSC-CMs) and maturation in culture, we isolated sub-cellular contractile organelles called myofibrils. Myofibril contractile kinetics from this line had slowed force development and cross-bridge detachment, with reduced maximal force compared to the WT line. hiPSC-CMs were cast into fibrin matrices to form three-dimensional, engineered heart tissue (EHT) for measures of twitch force and contractile kinetics. At 1Hz stimulation, heterozygous mutation EHT’s exhibited a hypercontractile phenotype compared to WT EHTs, with slowed relaxation kinetics. Since the penetrance of our heterozygous R403Q hiPSC-CMs is unknown, we are now studying a homozygous iPSC-CM line where 100% of the β-MHC is mutated. This will allow us to assess the direct contribution of the mutation to the disease contractile phenotype. We will repeat the myofibril and EHT measures of contractile properties and perform stopped flow kinetics analysis on isolated myosin to determine ATP turnover and ATP hydrolysis product release rates. This will provide molecular mechanistic insight of the contractile abnormalities, allowing development of therapeutic interventions that specifically target the mechanisms that alter contractile function. 

We are developing a RNA scaffold-based CRISPR activation and inhibition system to controllably tune gene expression in  primary immune cells, which will allow us to manipulate and increase production and function of immune cells, vastly increasing their efficacy in fighting diseases such as cancer. Here we target Bcl11b, a key T cell transcription factor necessary for progenitor cell commitment to the T cell lineage. CRISPR activation and CRISPR interference (CRISPRai) enable activation or repression of targeted genes. Due to the large size of dCas9 activator and reperessor fusions, it is not possible to express the necessary machinery in primary mouse T cells. Thus, we are developing a CRISPRai system where the gRNA (guide RNA) contains an additional RNA hairpin to recruit RNA binding protein-effectors, enabling activation and repression in the same cell. To optimize the efficiency of CRISPRi in T cells, we are 1) cloning and testing a repressor domain for its ability to drive gene silencing and 2) testing alternative RNA base pairs (BP) and hairpin pairs. We are testing these optimizations in a T cell progenitor cell line which has turned on Bcl11b with a downstream YFP (fluorescent) reporter. Here, YFP expression, which we measure using flow cytometry, is directly correlated to Bcl11b expression levels. We hypothesize that an alternative validated RNA hairpin BP in conjunction with a novel compact transcriptional effector will result in decreased levels of YFP expression compared to the existing system.

My project intends to discover a DNA aptamer, a single stranded DNA oligonucleotide, that binds selectively to the protein Interleukin-6 (IL-6). IL-6 has an important role in the immune system response and in excess it is known to cause inflammation. Aptamers exhibit binding affinities like that of antibodies but are ~50 times cheaper to produce. The method of aptamer discovery is through SELEX (Systematic Evolution of Ligands by Exponential Enrichment) which involves the selection from an aptamer library that contains 52N random nucleotide region and constant 5’ and 3’ 18 base pair regions for PCR amplification. Positive and negative selection are completed by incubating aptamer libraries with IL-6 or random protein immobilized on magnetic beads respectively. After each round selected aptamer sequences are amplified with a polymerase chain reaction (PCR) with primers that anneal to the constant regions. Reverse primer has biotin on 5’ end that is used later for strand separation with streptavidin agarose. After each round aptamer pool is going to be sequenced using nanopore sequencing platform till the enrichment of IL-6 specific sequences is observed. Binding will be tested through an enzyme-linked immunosorbent assay (ELISA) using the fam on 3’ end. The end goal of this project is to design a cost-effective method of IL-6 depletion from patients blood, allowing for cost-effective method of treatment for overactive immune system inflammation in sepsis patients.

The ability to manipulate and ligate proteins has been a driving force in advancing our understanding of the complex regulation of biological processes in space and time. Protein ligation, in which two or more polypeptides are covalently linked, is a powerful strategy in biomacromolecular engineering, enabling precise control over protein modifications, stability, and functionality. This is particularly useful in understanding protein function and interactions, as well as modulating protein activity, including immobilization of protein-based signals within materials triggered by cytocompatible light. One proven system known for its specificity and ease of use is SpyTag/SpyCatcher, a peptide-protein pair capable of irreversible ligation via isopeptide bond formation. Recent work has demonstrated the ability to control SpyTag/Catcher ligation using cytocompatible light due to its non-invasive nature and spatiotemporal (i.e., 4D control) manipulation of protein signals on a biologically relevant timescale. However, the application of this reported photoligation strategy is hindered by the use of genetic code expansion which limits protein yield, entails additional orthogonal protein machinery, and involves translational incorporation of a non-canonical amino acid. To address these challenges, we aim to develop a photocontrolled protein ligation strategy using native protein activity while maintaining spatial and temporal control. We predict this strategy will enable dose-dependent reconstitution of ligation by varying light exposure duration and intensity in native protein systems while sidestepping challenges associated with genetic code expansion. We intend to use this strategy to further assess our capability to control split protein reconstitution and for future applications in directing complex cell fate, which has significant utility in stem cell biology and regenerative medicine.

Cells in the human body contain the same DNA, and yet encompass an incredible range of structures and functions. This is possible due to genetic regulatory circuits that precisely control gene expression in response to external factors. While this is a central aspect of human biology, we lack a mechanistic understanding of how the majority of these regulatory circuits work. In this study, we investigate how the expression of Bcl11b, a gene that plays a large role in T cell development, is controlled by nearby noncoding DNA (referred to as a cis-regulatory element or CRE). We conduct a CRISPR interference (CRISPRi) screen in which a culture of P2C2 cells modified to express Bcl11b coupled to a fluorescent reporter protein is transfected with a guide RNA (gRNA) library that targets locations on the Bcl11b enhancer/promoter, and recruits repressive proteins to these sites. Cells transfected with gRNAs that bind to crucial regulatory locations experience a drop in Bcl11b expression that is measured via flow cytometry. These cells are analyzed using next generation sequencing techniques to determine which gRNA sequences are present, and thus which CRE sequences are the most essential for Bcl11b expression. In preliminary experiments, we have found that cis-regulatory elements at a distal Bcl11b enhancer, containing binding site locations of transcription factors controlling T cell specification, including T cell factor 1 (TCF-1), that play roles in controlling Bcl11b expression. The knowledge obtained from this experiment allows us to conduct future CRISPR gene expression studies in primary immune cells, where by precisely altering Bcl11b expression we can gain a mechanistic understanding of its effect on T cell development. This will drastically improve our ability to program human immune cells, resulting in medical advances such as far easier production of specialized T cells for cutting edge immunotherapies.

Tuberculosis (TB) remains the world’s deadliest infectious disease, claiming over 1.25 million lives annually—surpassing malaria and HIV in mortality. TB’s causative pathogen, Mycobacterium tuberculosis (MTB), continues to spread rapidly due to inadequate access to accurate molecular diagnostic tests. The most commonly used tests include sputum-based and tuberculin skin tests, which require follow-up visits and have suboptimal sensitivity, particularly within certain patient populations. Moreover, these assays cannot identify emerging drug-resistant strains (DR-TB) that have reduced susceptibility to first-line antibiotics. Our aim is to design a diagnostic tool to detect cell-free DNA (cfDNA) in urine and identify the infecting strain to ensure patients receive appropriate antibiotics. To achieve this, we are developing a probe-ligation assay with single-nucleotide specificity. Current implementations are limited by the low specificity of ligase, leading to false positives and an inability to differentiate between mutated MTB strains. We hypothesized that Flap Endonuclease-1 (FEN1) could confer a specificity advantage by integrating a second enzymatic “check” into the process. The protocol involves a ligation reaction with MTB genome-derived targets and two probes, each containing a DNA flap with additional nucleotides. To detect the ligated product, FEN1 must cleave these flaps before the ligase catalyzes the repair of the nick between probes. To experimentally observe this, we carried out several ligation reactions containing FEN1 and ligase with wild-type and mutant targets, followed by PCR or gel electrophoresis to measure ligated product formation. We evaluated the efficiency and precision by analyzing the amplification profiles of WT targets and mutants containing SNPs neighboring the ligation site. Our data about whether FEN1 confers a significant specificity advantage remains inconclusive, but the double enzyme reaction is functional and could be further exploited in future experiments with additional optimization or modifications to enzymes or DNA probes.

Optical coherence tomography (OCT) is a powerful non-invasive imaging technique, widely used for high-resolution 3-D structural imaging in research and clinical settings. Current variations, such as Point-Scanning OCT (PS-OCT), offer detailed structural images but require significant computational power for dynamic signal extraction, crucial for monitoring functional information like blood flow and cellular movement—key factors in disease diagnosis and treatment monitoring. The Biophotonics and Imaging Lab (BAIL) has developed an OCT angiography (OCTA) method for dynamic blood flow imaging. However, the OCTA system faces limitations due to its high computational demands. In this project, I propose an alternative approach using a Line-Scan OCT (LS-OCT) system, which samples lines within the region of interest to acquire simultaneous cross-sectional data. I aim to maintain dynamic signal extraction while reducing computational load and minimizing cell activity noise. If successfully developed, LS-OCT can revolutionize clinical melanoma diagnostics by providing real-time, non-invasive imaging of the epithermal and dermal information, thus identifying disruptions caused by tumor growth and angiogenesis without the need for traditional biopsies. The system will also have significant potential for real-time observations of drug effects on cancer cells, optimizing therapeutic testing by eliminating the reliance on histological processes. Specifically in this project, I will focus on designing an experiment to acquire live tissue data and process signals using the first LS-OCT system developed by BAIL. The goal is to compare dynamic image results with those obtained from PS-OCT systems, potentially enhancing future cell movement analysis research and supporting other PS-OCT-based projects requiring dynamic cellular information within living tissues.

Advancements in HIV prevention include pre-exposure prophylaxis strategies (PrEP), which are not as effective for women due to poor partitioning of antiretrovirals (ARVs) to the female reproductive tract. Integrating ARV-releasing reservoirs with intrauterine devices (IUDs) offers a strategy for local sustained delivery to overcome the partitioning issue. Our lab investigates reservoirs containing polymer-drug conjugates (drugamers), where the HIV integrase inhibitor raltegravir (RAL) is covalently attached to a polymer through a hydrolyzable linker. A previously characterized RAL-polymer exhibited release over 30 days, which is insufficient for the targeted 1-3 years of IUD-mediated delivery. To address this kinetic problem, the drugamer linker chemistry was modified from an ester to an acetal carbonate. Since the rate-determining step of the acetal carbonate linker hydrolysis does not depend on the acidic RAL hydroxyl (pKa = 6.6), it was hypothesized that this acetal carbonate linker will slow the RAL release rate as opposed to the ester linker. An acetal carbonate-linked monomer of RAL was synthesized and led to a 30-fold reduction in hydrolysis rate. The corresponding drugamer was then synthesized via RAFT polymerization and characterized via NMR. In hydrophilic media, RAL released from the novel polymer significantly slower than in the current lab polymer, showing potential for lengthened duration of action in in vivo models. Future work includes measuring release from RAL-polymer in a matrix device for future IUD incorporation, assessing potential polymer cytotoxicity, and evaluating release rates in mouse models. These findings lay the groundwork for the development of long-acting formulations for sustained HIV prevention.

VLA-4 is an integrin expressed on immune cells that plays an important role in their extravasation into tissues during an immune response. In the autoimmune disease multiple sclerosis (MS), pathogenic T cells extravasate and attack nerve cells by using VLA-4 to bind to VCAM-1, a cell adhesion molecule on endothelial cells that line blood vessels. Current treatments for MS rely on antibodies to bind VLA-4 and block its interaction with VCAM-1, thus preventing a pathogenic immune response. However, antibodies are expensive to manufacture, and their binding cannot be easily regulated to control drug-induced side effects. Aptamers are single-stranded DNA or RNA molecules that fold into sequence-defined structures capable of binding to their targets with affinities and specificities comparable to antibodies. Being chemically synthesized, they are much cheaper to manufacture and offer minimal batch-to-batch differences. Unlike antibodies, their binding in vivo can be rapidly reversed using a reversal agent, which could alleviate the side effects of disease treatments. However, aptamers have limitations in vivo: degradation by nucleases in blood serum, and rapid clearance into urine through the glomerular filtration barrier. This project focuses on the development of a VLA-4 aptamer for treating MS. We found that the VLA-4 aptamer prevents soluble VCAM-1 from binding to VLA-4-expressing leukocytes by flow cytometry. We then showed that the aptamer blocks VLA-4/VCAM-1 mediated leukocyte adhesion in vitro. We are currently assessing aptamer blockade of leukocyte transendothelial migration. We are also designing modifications to improve the stability of the aptamer for in vivo uses. Successful development of the aptamer will lead to an alternative treatment modality for MS with a potentially improved safety profile.

Traumatic brain injury (TBI) is one of the leading causes of death in young adults. It is initiated by loss of endothelial junctions during deterioration of the blood-brain-barrier. Investigation into endothelial barriers has been enabled by high-resolution imaging via confocal microscopy. However, existing image analysis tools struggle to capture the complexity of EC morphology due to their reliance on rigid segmentation, limiting their ability to extract meaningful insights. My project focuses on developing a more effective method for analyzing ECs by implementing a pixel-based computational tool that provides a more nuanced analysis of EC junction integrity and morphology beyond traditional segmentation methods. Immunofluorescence (IF) images were obtained from an in vitro model of TBI mimicking 3D brain microvessels which were treated with kinase inhibitors (KIs) to determine which kinases promote or hinder recovery. If ECs remained damaged after treatment, it indicate the inhibited kinase was essential for recovery. If they improved, the kinase was likely disruptive. To identify these effects of KIs on EC based on IF images, I developed a pixel-based clustering tool that analyzes junction intensity without forcing explicit segmentation. By analyzing pixel intensities relative to cell nuclei, I generated profiles of each vessel that represent the tightness of EC junction. I used an existing AI-based tool, Cellpose, to define nucleus masks and wrote a customizable Python script to compute pixel distances and intensity variations, providing a detailed, unbiased view of EC behavior. Preliminary findings suggest that this method enhances the accuracy and efficiency of cellular analysis by eliminating segmentation bias and capturing subtle morphological changes. Future work involves integrating this tool with regression models to identify kinases that regulate EC junction integrity. This research has broad applications in vascular disease modeling and drug discovery, offering a new approach for studying cell behavior and developing targeted therapies. 

Neurodegenerative disorders, including Alzheimer’s, are characterized by the accumulation of fibril aggregates—made up of amyloid β-sheet peptides—which were historically thought to disrupt cellular function and contribute to neuronal death. Recent studies have revealed that these plaques are relatively benign; they are preceded by toxic oligomers—peptides that adopt a rare α-sheet secondary structure. These oligomers form decades before the appearance of plaques and have been linked to the neurodegenerative symptoms associated with these diseases. As precursors to full aggregates, toxic oligomers serve as valuable therapeutic and diagnostic targets. Custom peptides designed to bind to α-sheet toxic oligomers can be deposited onto the surface of a well plate to form the basis of a diagnostic assay. Similar to a sandwich ELISA, this soluble oligomer binding assay (SOBA) utilizes a two-antibody system to selectively detect the presence and relative concentration of α-sheet oligomers. In an effort to improve assay repeatability, we attempt to optimize the antibody system used in SOBA experiments. To evaluate assay performance, we test a variety of incubated Aβ oligomer samples and brain homogenates from transgenic mouse models to assess SOBA sensitivity and specificity. In the future, we aim to extend SOBA repeatability studies beyond Alzheimer’s to other aggregation-related disorders, such as type two diabetes and Parkinson’s. By improving the repeatability of this assay, we can enhance early detection methods for Alzheimer’s and related disorders. These experiments serve to develop a standard method for the detection of toxic oligomers, which could pave the way for future neurodegenerative disorder treatments and diagnostic strategies.

Architectural and spatiotemporal aspects of epigenetic regulation and cell behavior are critical for maintaining overall health. Unintentional genetic mutations can create dynamic dysregulation in the epigenome and transcriptomes at the cellular level which is implicated in diseases ranging from fibrosis to cancer. However, our tools to probe and understand these behaviors are limited by a lack of spatiotemporal control. To address this, we propose installing four-dimensional control over the potent CRISPR inhibition transcriptional effectors to establish epigenetic control at cellular scale resolutions.  CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is a genetic modification system that relies on Cas9 proteins to splice and deactivate genes as controlled by a programmable guide RNA sequence. CRISPR inhibition relies on a deactivated Cas9 protein that does not directly alter the genetic material in order to sterically hinder transcription. Our work aims to formulate a CRISPR inhibitor system which can unbind from the target DNA with two photon activation via a photo-cageable noncanonical amino acid insertion. This would allow for four-dimensional spatiotemporal control over the system, thus increasing the level of control in epigenetic regulation. Currently, work is being done to test the CRISPR inhibition system in HEK 293 cells that have been lentivirally transduced with both a test sequence and the deactivated Cas9 protein. After testing is completed for this simpler system, we will move toward creating a system that incorporates the photocaged noncanonical lysine variant, giving us control over the CRISPR inhibition system with regards to both space and time.

Biological processes rely on the intricate functions of proteins, which drive essential biochemical reactions. Given their critical role, various methods have been developed to regulate protein functions in biomaterials and in vitro. Enhancing the precision of gene editing is crucial for advancing applications in gene therapy and minimizing off-target effects. My project focuses on integrating photoactivatable proteins with prime editors, a modified version of the widely known gene editor CRISPR/Cas9, to improve spatial and temporal control over gene modifications. By utilizing genetic code expansion, non-canonical amino acids are incorporated into human cells to express photocaged prime editor proteins and altering host genomes. This system enables optical stimulation to precisely regulate protein activity. Through the deployment of well-characterized photolabile groups, we expect to be able to render protein activity controllable in a dose dependent way. A key application of this approach is the development of a photoactivatable prime editor system to induce precise gene edits. Traditional CRISPR/Cas9 methods lack spatiotemporal control over activation. To address this, the system is adapted for use in hydrogels, where two-photon patterning allows visualization of prime editor protein activation in three dimensions. Our study aims to demonstrate the feasibility of optically controlling gene editing with high specificity, offering a novel strategy for advancing cell lineage tracing and gene therapy applications.

Nanoparticles are drug delivery carriers on the nanometer-length scale, and are promising targeted drug delivery solutions due to their small size and tailorability. However, current materials used to produce nanoparticles are synthetic and typically lead to large amounts of chemical waste and high costs. To explore more sustainable technologies, the Nance and Roumeli labs established a novel bacterial cellulose nanoparticle (BCNP) platform. BCNPs are formulated with a bacteria that produces cellulose and no byproducts when cultured, allowing for less reagents required and non-toxic biodegradable wastes. To be comparable to synthetic nanoparticles as a drug delivery platform, BCNPs must load and release drugs and be biocompatible with mammalian cells. In this project, I explored the tunability of BCNPs through size modification, performed cytotoxicity studies on a microglial cell line, and carried out drug loading studies. I found that higher mixing speeds during BC culturing led to a smaller BCNP size and variable particle concentration. Through cytotoxicity analysis in cell culture, I showed BCNPs were not toxic. Ongoing studies are assessing BCNP cytotoxicity as a function of BCNP dose. To demonstrate drug loading, I am incorporating catalase, an enzyme with the ability to mitigate oxidative stress markers, into BCNPs to analyze their efficacy in an in vitro model of oxidative injury. These results show BCNPs have the potential to become a sustainable nanomedicine platform and provide an important step towards reducing the environmental impact of synthetic nanoparticles.

Tumor angiogenesis is characterized by unregulated blood vessel formation, impairing vascular networks and biological transport. It represents a critical stage in cancer progression, where malignant tumors metastasize and exploit the human body’s resources, which lie in vascular networks. However, the complex tumor microenvironment presents significant challenges in studying tumor angiogenesis and identifying its biomarkers. Towards addressing this concern, hydrogels—water-swollen, polymeric networks—can be used to recapitulate the tumor microenvironment, whose physiochemical properties can be precisely tuned to match that found in vivo. The DeForest Lab has developed methods and techniques in bioorthogonal chemistry and light-based subtractive manufacturing to tune such hydrogel materials with precise and unique 4D control, all at subcellular resolutions. In this project, I will exploit image-guided multiphoton lithography to engineer natively complex tumor vasculature patterns within photodegradable hydrogels. We will further embed tumor vascular spheroids within these hydrogels, providing a platform to model and assay tumor progression in vitro. This study has exciting implications for translational research and preclinical studies, particularly for disease modeling and therapeutic screening, as well as reducing ethical concerns regarding tissue and animal models in preclinical studies.

Hydrogel biomaterials have many applications in tissue engineering and drug delivery. Stimuli-responsive hydrogels allow for controlled drug release, dependent on a user-defined trigger. However, current stimuli-responsive hydrogels are case-specific and cannot be used for broader applications, such as targeted disease treatment. Most hydrogels can only respond to one input, making them difficult to use in treating diseases with multiple markers. We developed a fully recombinant protein-based material with protease degradable cross links that follow Boolean logic (YES/AND/OR) in response to multiple inputs to allow for user controlled material degradation and drug release. The protease degradable sequences can be easily switched out before expression depending on the application, making our hydrogel generalizable. The hydrogel will be crosslinked with Boolean logic constructs, each of which are flanked by a click-like chemistry protein system. This allows the crosslinks to be covalently ligated to a linker made from elastin-like polypeptides (ELP), which holds the hydrogel network together. The crosslinks and ELP were expressed recombinantly in E. coli and purified on an ӒKTA Pure (Cytiva). A degradation study was conducted by adding different combinations of proteases to prove that material degradation is dependent on the combination of proteases added. We then conducted rheometry to determine the mechanical properties of the hydrogels, and verified that material stiffness followed the expected logical operation, where correct inputs resulted in material degradation. Finally, we tested the hydrogel’s ability to release drugs by incorporating human epidermal growth factor (hEGF) into the gel and measuring activation of the ERK signaling pathway through a Western Blot. The Western Blot showed activation of the ERK pathway only when the correct combination of proteases was added, indicating release of a bioactive protein drug. If successful, this hydrogel could be used for therapeutic delivery of drugs and broader tissue engineering applications.

User-controlled cell behavior is useful for studying wound healing because the isolated therapeutic effects of individual signals can be observed at the wound site. Aptamers are single-stranded oligonucleotides that fold into three-dimensional structures that can capture and inhibit proteins. The biological capacity of cells to deploy traction forces as a release mechanism for extracellular proteins can be engineered through clever deployment of aptamer-bound proteins with peptide handles. Scientists at the Imperial College London recently synthesized TrAPs: Traction Force-Activated Payloads that enable precise control of cell behavior using such a strategy. We bound photocaged TrAPs lacking adhesion handles to functionalized collagen hydrogels. Peptide immobilization was then selectively patterned using 365 nm light to spatially confine cell access to captured vascular endothelial growth factor (VEGF). After surface seeding endothelial cells, observations were made regarding changes in cells’ physical characteristics as a result of  protein release. Through SELEX (Systematic Evolution of Ligands by Exponential Enrichment), TrAPs can be designed for any target protein in the extracellular matrix. The wide scope and biorthogonality of this project allows for many applications in medical technology and user-controlled cell fate. 

Mild hyperthermia - defined as raising the human body temperature to 39-42 Celsius - has been shown to improve the effectiveness of systemic therapies for cancer treatment by improving tumor oxygenation and blood flow. High intensity focused ultrasound (HIFU) is a non-invasive, thermal ablative therapy that can be used to induce mild hyperthermia in a small area around the focus. When used in the presence of microbubbles (an ultrasound contrast agent), referred to as bubble-enhanced heating (BEH) HIFU becomes more efficient and increases the treatment area. Further research is required to study the mechanisms of BEH and better understand the complex relationship between microbubble dynamics and the ultrasound parameters. In this in vitro study, I fabricated gel and liquid tissue-mimicking phantoms to perform heating experiments in. The experimental setup consisted of a focused ultrasound transducer aligned to two thermocouples that were placed inside the phantom, one at the focus and one pre-focally. An imaging probe was used to image the phantoms before and after HIFU exposure. During heating experiments, I measured the temperature of the phantom at a single point via thermocouples for 30 s of continuous ultrasound exposure followed by 30 s after exposure has been stopped. I originally hypothesized that as microbubble concentration increases, the temperature elevation would also increase. However, the results showed that for both the gel and liquid phantoms measured at the focus, a higher microbubble concentration does not always result in a higher temperature elevation. This is due to the phenomenon of acoustic shadowing, where the concentration of microbubbles impedes the propagation of sound through the phantom, altering where most of the heat deposition occurs. Future experiments will be performed to confirm these results and investigate further microbubble concentrations and acoustic pressures in order to optimize BEH treatment for future clinical applications.

Chimeric antigen receptor (CAR) T-cell therapy offers a promising approach to cancer treatment by harnessing the immune system to target and destroy tumor cells that express a specific cell-surface antigen. While CAR T-cell therapies have been successful in treating blood cancers, their efficacy against solid tumors is limited due to tumor antigen heterogeneity. To address this challenge, we have engineered a universal SpyCatcher003 CAR T-cell system (DB5 CARs) that utilizes synthetic peptide intermediates to target multiple antigens. Peptides are high-affinity biomaterials capable of binding receptors expressed on cancer cells for targeted T-cell killing, but peptides are limited by a short half-life due to rapid degradation in vivo. To overcome this challenge, we have developed peptide co-polymer formulations that are multivalent and exhibit increased serum stability. Additionally, the chemical and structural functionality can be tuned to precisely control the molecular weight and the number of peptides per polymer, enabling simultaneous and multivalent CAR engagement on T cells. In this project, we aim to characterize the serum stability and improve bifunctional loading and targeting of SpyTag003-peptide and folate co-polymer formulations. Preliminary studies demonstrate that SpyTag003 peptide co-polymer intermediates efficiently load onto CARs and exhibit enhanced binding to cancer cells. We hypothesize that SpyTag003 peptide co-polymer intermediates will display superior CAR T-cell activation compared to SpyTag003 peptide intermediate in vitro. We evaluated the serum stability of folate-modified peptide co-polymer intermediates to confirm their enhanced functional half-life and stability. In addition, we assess the cytokine expression and cytotoxic activity of CD4+ and CD8+ DB5 CAR T cells pre-armed with folate-modified peptide co-polymer intermediate. If successful, our approach for universal CAR T-cell therapy could address critical limitations in current CAR T-cell therapies by providing a more comprehensive and durable strategy for targeting heterogeneous solid tumors, ultimately improving treatment outcomes for patients.

Nearly all forms of cardiac disease are characterized by cardiac fibrosis, which contributes to heart failure and arrhythmias due to the accumulation of collagen deposits. Collagen, a crucial extracellular matrix (ECM) protein, is secreted by cardiac fibroblasts—the primary cell type responsible for generating this stiff scar tissue known as fibrosis. Fibroblasts are highly plastic cells that can transition between quiescent and activated states. The Davis Lab has developed a minimally invasive intermittent injury model to cyclically stress cardiac fibroblasts in vivo, allowing for a deeper investigation into the role of cellular memory in regulating the fibrotic response. Notably, we can reduce fibrotic remodeling in this model by inhibiting p38 gene function in the activated population, thereby encouraging a shift back to a quiescent state. My work aims to determine whether the once-activated population is proliferating at the second injury stimulus as well, or if a new population of fibroblasts is proliferating with repeat injury. To address this, I am utilizing genetic lineage tracing and Click-iT EdU technology, which allows for precise biolabeling while also preserving cell morphology and integrity by integrating into the cell's DNA. I am also performing immunohistochemistry staining to detect other proteins of interest that will serve as proliferation markers as well. Based on prior findings in the Davis Lab, we hypothesize that once-activated fibroblasts will go on to activate again when exposed to repeated disease stimuli, but there will be no second wave of proliferation as there was no change in total fibroblast number. 

The ecosystem of microbes found in the gut, or the gut microbiota, plays a vital role in host health, influencing the immune, digestive, and central nervous systems. Research suggests that the microbiome may be linked with the development of neuropsychiatric disorders, presenting the possibility that altering the microbiome could influence the risk of these conditions. Recent research has explored this link within the context of Parkinson’s Disease (PD), a neurodegenerative disorder primarily known for its effects on motor control. PD patients often suffer from chronic constipation for years prior to diagnosis. Although the mechanisms of this gut-brain relationship are still unknown, many studies have highlighted the potential involvement of the gut microbiome in the development of PD. I explored the specifics of this relationship by developing a metabolic model trained on metagenomic data from PD case-control studies, using a microbial community-scale metabolic modeling (MCMM) approach. MCMMs may provide detailed mechanistic insights into the gut-associated etiology of PD, potentially allowing for the development of preventative therapies that prevent the onset of PD, which could revolutionize our current system of retroactive treatment of the established disease.

Heart disease is linked to one in every five deaths in the United States, indicating the need for more research on causes and possible treatments. Dilated cardiomyopathy (DCM) is an inherited cardiomyopathy characterized by a decrease in contractile function, which often leads to heart failure and death. DCM is a disease of progressive remodeling and is often not diagnosed until later in life once a patient becomes symptomatic and the progression of disease is difficult to discern. By understanding the specific molecular etiology of DCM, treatments can be specialized and better prevent progression to end-stage heart failure. One protein associated with DCM is the motor protein myosin. In the Regnier Lab, we study the dilated cardiomyopathy-associated myosin mutation R369Q to better understand the molecular mechanisms leading to DCM. To explore this, I used Human Induced Pluripotent Stem Cells (hiPSCs) that have been CRISPR-edited to contain the mutation, differentiated into cardiomyocytes and cultured on patterned surfaces to promote maturation and alignment of the contractile organelles called myofibrils. I electrically paced and live-imaged these cells to capture single-cell contraction to compare differences in sarcomere shortening and quantify cell-level effects of the R369Q mutation. I also analyzed flat glass imaging to measure cell area and potential differences in sarcomere alignment. My goal is to better understand how the structural and functional differences on a single cell level fit into the context of a DCM mutation's effects in the heart. Ultimately this will allow a better understanding of the R369Q mutation’s pathogenic effects and give better insight into how possible future treatments can potentially combat the effects of DCM.

Therapeutic ultrasound with microbubble contrast agents induces biological effects that can be utilized for various clinical applications, and its non-invasiveness enables targeted treatments without harming tissue around the target by concentrating the acoustic energy of ultrasound to a specific location. In cancer therapy, ultrasound can enhance the delivery of chemotherapy by priming tumors or directly destroy cancer cells without surgical risks. While Averkiou lab investigates the effects of ultrasound pulses with microbubbles to enhance the efficiency of drug delivery into cancer cells, this project focuses on studying microbubble behavior during ultrasound-microbubble therapy and developing a technique to monitor their response and effects on surrounding tissues. A tissue-mimicking phantom with a wall-less channel will be used to simulate a vascular environment, allowing for controlled observation of microbubble cavitation. Passive cavitation detection (PCD) will be employed to monitor microbubble responses, with one transducer delivering ultrasound pulses to excite microbubbles and another transducer passively recording the resulting scattered signals. Additionally, this study will explore how excitation pulse nonlinearity influences microbubble behavior by modifying the acoustic conditions. While prior research has primarily focused on peak negative amplitudes when transmitting acoustic pressure, this project will examine the effects of both peak negative and positive amplitudes, potentially revealing new insights into microbubble dynamics and therapeutic ultrasound applications. Differences in microbubble responses to these excitation pulses will be analyzed experimentally and compared to theoretical predictions using MATLAB-based computational simulations. The findings of this study could contribute to optimizing ultrasound-mediated drug delivery and broadening the clinical applications of therapeutic ultrasound.

Internal pressure sensing gives healthcare providers essential information regarding patient health and can help determine risk factors for many diseases. The current method for this involves the insertion of a catheter to the location where pressure is being measured (e.g. portal vein, cranium, spine), which can be an invasive and potentially dangerous surgical procedure. A promising alternative is to use ultrasound contrast imaging and microbubbles as a pressure sensor. Studies have shown that the magnitude of the subharmonic component of scattered signals from microbubbles varies as ambient pressure changes. However, many acoustic parameters can induce this effect and it is still unknown how to optimize the parameters to maximize the subharmonic response. I perform experiments to determine the ideal acoustic parameters to sense these changes in ambient pressure and apply this knowledge to develop an ultrasound imaging system that can predict these pressures in vitro.

Liver cancer can be diagnosed in the clinic with contrast-enhanced ultrasound (CEUS). This method of diagnosis is qualitative and relies on the comparison of blood flow in the suspected tumor to the rest of the liver. However, observer biases in this method can result in inaccurate diagnoses and delays in treatment. To reduce observer bias, our lab developed a comprehensive and repeatable method of quantifying blood flow in liver tumors from CEUS scans. One problem that reduces the accuracy of this quantitative CEUS method is that tumor blood flow metrics are highly impacted by the motion of the liver, stemming from both breathing and sonographer movement. To solve this problem, there needs to be a standardized method to both detect and correct the motion of the tumor on the CEUS scan. I created an automated MATLAB algorithm to measure the motion of a suspected liver tumor on a CEUS scan and identify frames that cannot be analyzed quantitatively. Compared to a manual realignment and deletion of frames done by an expert (a very time-consuming process), as well as a current motion reduction algorithm based only on respiratory gating, my algorithm was simpler, faster, required less input, and produced similar blood flow parameters. This suggests that my MATLAB algorithm can be used in combination with quantitative CEUS processing to help clinicians diagnose liver cancer more rapidly and accurately.

Functional assays on intact tumor biopsies play a key role in drug testing, personalized oncology, and cancer research by allowing scientists to better characterize tumor biology. However, these assays usually rely on antibody-based fluorescent labeling. Fluorescent labeling, while well-researched and reliable, is labor-intensive, semi-quantitative, and cannot provide real-time data. In this project, we designed and created a sensor that addresses these issues by using electrochemical aptamers. Our sensor features a 24-well, multiplexed electrochemical setup that detects concentrations of Cytochrome C (CytC), a cell death indicator, with high affinity and specificity. We found that we were able to quantitatively track increasing CytC concentrations in real time as microdissected tumor samples were being treated with various cancer drugs. In the future, this sensor could be expanded to work with more biomarkers, paving the way for clinical use, real-time tumor response monitoring, and high-throughput oncology drug screening.

Tetralogy of Fallot (TOF) is the most common cyanotic congenital heart defect and consists of four structural defects that prevent babies’ hearts from delivering oxygenated blood to their body. When life saving surgeries correct these defects, the resulting scar changes the way the heart conducts electrical impulses, causing abnormal heart beats later in life. These abnormal heart beats, arrhythmias, often present as sudden cardiac arrest. Due to the high risk of arrhythmias in patients with repaired TOF, it is clinically important to understand the exact mechanisms causing them. These mechanisms provide insight that is essential to developing personalized methods for preventing arrhythmias. In our lab, we use late gadolinium enhanced MRI scans from TOF patients to create personalized computational models of their heart and particular scar distribution. We then attempt to induce arrhythmias in our models, which are individualized and represent subcellular and cell-scale electrophysiological phenomena. These models are useful because they allow us to study arrhythmia mechanisms noninvasively. We expect that patients whose computational models are susceptible to arrhythmias will also be more likely to experience arrhythmias in real life. We also aim to use the mechanistic insights from these simulations to determine new ways of predicting arrhythmia risk in this vulnerable patient population. Our results should predict what subset of patients would benefit from invasive preventative procedures, and help give patients with TOF a better understanding of their personal risk with or without those procedures. We hope to use our methods and results to create a simple and accessible arrhythmia risk stratification tool.

Ayurvedic home remedies have been utilized for centuries as effective and accessible solutions for a wide range of health conditions. However, their use remains unknown in Western medicine due to limited understanding and scientific awareness. This review aims to bridge this gap by providing scientific reasoning and research behind three commonly used Ayurvedic remedies: Tulsi (Ocimum sanctum) for managing fevers, Turmeric (Curcuma longa) for alleviating arthritis, and Ashwagandha (Withania Somnifera) for stress management. These remedies not only offer an alternative to conventional medicine but also address critical barriers such as cost, accessibility, and empowering the body’s natural ability to heal. By highlighting the mechanisms of action, clinical efficacy, and safety of these remedies, this paper seeks to justify their use to a western audience, while alleviating misconceptions about allopathic medicine. The findings underscore the potential of Ayurvedic remedies as cost-effective and viable options for individuals facing challenges such as limited mobility or financial constraints. Ultimately, this work advocates for the integration of scientifically validated Ayurvedic practices into modern healthcare to provide a holistic and affordable approach to wellness.

The project aims to engineer a new µMASS sensor with increased baseline fluorescence and improved dynamic range by applying linker optimization and subsequent high-throughput screening. µMASS is a genetically encoded fluorescent indicator that, when bound to an opioid, changes conformation, causing an increase in fluorescence intensity. µMASS is a tool that enable real-time imaging of opioids in the brain, allowing researchers to study neural pathways involved in addiction. While the sensor can detect opioid ligands in vitro, it requires optimization for use in vivo to study real-time opioid release. Linker optimization is a technique that involves introducing mutations into the linker region of the sensor. I hypothesize that mutating the linker residues will enhance the conformational change observed in µMASS-5-HT upon opioid binding while retaining enhanced baseline fluorescence.

Engineered heart tissues (EHTs) have emerged as a promising tool for cardiac disease modeling and drug screening, allowing for better study of heart diseases (HDs). However, most current EHTs are composed of only a mixture of an extracellular matrix, heart muscle cells, called cardiomyocytes (CMs) and cardiac fibroblasts, without a vascular element. This prevents the study of the impacts of flow and the endothelium on cardiac function, despite their important role in both development and disease progression. Endothelial cell (EC) function is essential for maintaining cardiac homeostasis through protective signaling interactions between ECs and CMs. Disruption of endothelial function through vascular stressors such as hemodynamic changes and acute inflammation can trigger EC dysfunction, dysregulating cardioprotective signaling. It is important to incorporate the endothelial and perfusion components in EHT in vitro for better disease modeling and drug testing. The Zheng lab has developed a tube-like perfusable collagen-based EHT model, where CMs are embedded in the bulk collagen matrix, and the inner lumen of the tube can be endothelialized, serving as an effective, in vitro, model of cardiac vasculature. This project controls the size of the inner tube diameter of this model utilizing structural and contractile properties of muscle cells. Through the integration of these cells, we can maintain the inner diameter under a range of flow conditions, and subsequently use the model to identify healthy and unhealthy flow conditions within the EHTs. This project establishes a perfusable EHT model that allows us to examine EC function under several flow-related changes and, in the future, assess the effect of endothelial dysfunction on cardiac function.

In the Berndt lab, we develop genetically encoded fluorescent indicators (biosensors) by attaching a naturally occurring sensing domain to a fluorescent protein. When the ligand of interest, such as dopamine or calcium, interacts with the sensing domain, the protein will undergo a conformational change that induces a fluorescent response. The change in fluorescence can be measured and used to quantify biochemical activity. Applications of these biosensors span a wide range of research topics in neuroscience and behavior, providing insights into the neuronal network activity correlated with addiction, pain perception, emotion, and reward signaling. The current project that I am working on is optimizing the red dopamine sensor, GRABrDA2m. I developed a genetic library, mutating the linkers that connect the sensing domain and fluorescent protein. The behavior of proteins is highly dependent on structure and orientation, which is why I have chosen the linkers as a target region to explore. I have cloned in degenerate codons that randomize the nucleotides at specific positions on these linkers, with the linker locations having been recently identified in published literature. After sequencing the DNA to validate that the sites of interest were mutated appropriately and that the remainder of the sensor is intact, I will transfect these plasmids into human embryonic kidney 293 (HEK293) cells and screen for promising variants by employing OptoMASS, an cell array technique developed in the Berndt Lab that allows for the testing of hundreds of mutations simultaneously. I will pick out the cells whose sensors performed better than the parental variant, looking for improvements in baseline fluorescence and sensitivity to dopamine, then conduct reverse-transcriptase polymerase chain reactions to extract the sequences of the high-performing sensors.

The increasing rise in allergy prevalence has led to a growing demand for portable allergen testing devices. Food allergens, which can lead to fatal immune reactions, are especially complicated to avoid due to cross contamination and food mislabeling, as seen with many types of seafood. Instances of seafood mislabeling and inauthenticity also impacts consumers financially when cheaper options are passed off as more rare and expensive fish. Atlantic salmon is one of the most commonly used fish for this type of fraud. Devices to detect allergens and/or authenticity must be easy-to-use, quick, and require little to no dangerous reagents for the regular consumer. While there are some commercial devices on the market for peanut and gluten detection, they are costly and do not appear to be very accurate or sensitive. Our prior work showed a proof of concept for a one-pot amplification-detection method with recombinase polymerase amplification that allowed for a reaction to occur at a fixed temperature and with no expensive laboratory equipment. Currently, I am developing fluorescence-based polymerase chain reaction and recombinase polymerase amplification assays that can differentiate Atlantic salmon from other types of salmon. To further develop this technology into a consumer-friendly allergen detection and seafood authentication device, I plan on adapting the assay into an electrochemical format, allowing for simplified readouts of the results. The results from this assay would be able to be displayed on easily accessible electronic devices, such as a smartphone or laptop. In its final form, this project will demonstrate a portable heating device with a classification assay that would be able to detect the presence of Atlantic salmon without laboratory equipment.

Treatment-related cardiomyopathy is a significant cardiotoxic complication for cancer patients treated with chemotherapy or radiotherapy and a leading cause of premature morbidity in childhood cancer survivors. Predicting a patient’s cardiomyopathy risk could help clinicians intervene early but is not possible with standard echocardiogram analysis methods. Preliminary research at the CardSS lab demonstrated that a deep convolutional neural network has modest success at predicting a pediatric patient’s risk for developing CM but is significantly limited by insufficient pre-diagnosis data for training, impairing its ability to learn generalizable disease progression patterns. This research aims to develop a generative AI model that generates synthetic echocardiogram data for training to improve the prediction model’s ability to learn distinctive patterns representing cardiomyopathy risk. By training on a longitudinal dataset containing echocardiograms from several cardiomyopathy stages before diagnosis, we aim to produce synthetic echocardiograms conditioned on specific classes: 0-1 years before diagnosis, 1-3 years before diagnosis, cardiomyopathy present, and control. Thus far, I have preprocessed echocardiogram data and implemented three experimental diffusion model architectures to investigate how the addition of a cross-attention layer to the encoder, bottleneck, and decoder regions of the model affects its ability to produce echocardiograms of different classes. I also implemented an analysis pipeline that calculates the Fréchet Video Distance (FVD), Structural Similarity Index Measure (SSIM), and Peak Signal-to-Noise Ratio (PSNR) between two sets of echocardiograms, which provide measures of image/video similarity. Using this pipeline, I am evaluating two key standards for synthetic data—intraclass fidelity and interclass separability—to quantify each model’s ability to generate data that is (1) representative of its class and (2) distinct from data produced for another class, and how these metrics change as training progresses. Preliminary data has shown that these models are producing synthetic echocardiograms that closely resemble real echocardiograms, but inconsistently.

Estradiol, a steroid hormone, plays a crucial role in bone density, cardiovascular function, and neuroprotection. It signals through Estrogen Receptor α (ERα), a nuclear receptor that, upon estradiol binding, undergoes a conformational change, translocates to the nucleus, and regulates gene transcription. While ERα's role in gene regulation is well established, the real-time kinetics of estradiol signaling remain poorly understood. To address this, I have been developing and optimizing a fluorescent biosensor, ER_mNG, to enable real-time monitoring of estradiol levels in living cells. ER_mNG consists of ERα’s ligand-binding domain (LBD) inserted within the mNeonGreen fluorescent protein. Estradiol-induced conformational changes in ERα alter mNeonGreen’s fluorescence, providing a readout of estradiol dynamics. To improve the sensor’s dynamic range, I have employed linker optimization, a structure-guided protein engineering approach. I designed and cloned ER_mNG variants with modified linker lengths and amino acid compositions using site-directed mutagenesis and in vivo assembly (IVA) cloning. These variants were transiently expressed in HEK293 cells via lipofection, and their fluorescence response to estradiol stimulation was quantified using live-cell fluorescence microscopy. By systematically modifying the sensor’s structure, I aim to develop an improved ER_mNG variant with a significantly enhanced dynamic range, enabling more precise measurements of estradiol signaling. This tool has the potential to advance our understanding of estradiol’s role in health and disease.

Bacterial cellulose (BC) nanoparticles (BCNPs) are a promising sustainable nanomedicine platform for drug delivery and provides a scalable, eco-friendly alternative to synthetic counterparts. We aim to develop a small library of BCNPs with different chemical moieties to incorporate a broad range of active agents for drug delivery use. To produce BCNPs, a BC pellicle is grown in a kombucha media of tea, sugar, vinegar, and bacterial co-cultures. The pellicle is isolated and chemically and manually broken down using dimethylacetamide, lithium chloride, and an ultrasonicator probe to produce an organic BC dissolution. The BC dissolution is precipitated into an aqueous Pluronic F-127 (F127) surfactant solution under 650 rpm stirring conditions and incubated for 2 h to form nanoparticles ~100 nm, near neutral charge, and low polydispersity index (<0.3). In this study, we optimize the dissolution and nanoprecipitation processes using acetylated and methylated BC pellicles to form acetyl- and methyl-functionalized BCNPs. The functionalized BCNPs were characterized using Fourier transform infrared spectroscopy, nanoparticle tracking analysis, electron microscopy, and light scattering to assess physicochemical properties. Our results demonstrate that functionalized BCNPs can be formulated using similar formulation parameters to unmodified BCNPs. Ongoing work evaluates drug loading and encapsulation efficiencies in the functionalized BCNPs using curcumin as a model drug. Engineering BCNPs with different chemical moieties enables incorporation of a wider array of drugs, which can improve the utility of BCNPs as a sustainable alternative to current synthetic nanomedicines.

Chloramphenicol (CAP) is a synthetic antibiotic used to treat various bacterial infections in animals and humans. However, case studies and clinical trials have revealed that CAP can induce severe blood disorders, genotoxicity, and carcinogenic effects. Consequently, in 1997, the United States and several other countries prohibited its use in food-producing animals and imposed strict regulations on its application in human healthcare. Despite regulations, CAP remains prevalent in food, especially in imported seafood like shrimp, posing a risk to human health. To address this issue, we aim to develop a CAP contamination-detection assay using two engineered DNA strands: a CAP-specific aptamer and a blocker. Using NUPACK, a Python package for thermodynamic analysis of nucleic acids, we created scripts to design, select, and evaluate candidate DNA strands from our sequence library. We are developing a two-phase assay to assess their specificity and sensitivity to CAP. In the first phase, blockers are tagged with a fluorophore, and aptamers are conjugated with biotin and a corresponding quencher. These sequences are incubated in streptavidin-coated wells, and the aptamer-blocker separation is measured via fluorescence when aptamers more favorably bind to CAP. In the second phase, the released blockers are collected, amplified, and detected using recombinase polymerase amplification (RPA) with exonuclease III and target-specific probes. Unlike the first phase, the aptamers remain biotinylated with no fluorophore-quencher conjugation, as target-specific probes have their fluorescence mechanism. In the future, this assay will be streamlined and used in conjunction with point-of-care applications to detect other small molecules.

Hydrogels with tunable stiffnesses are a versatile method to study the interactions of human cells in vitro. These systems recreate human extracellular matrix (ECM) and capture the stiffness changes associated with a variety of biological processes and diseases, like cancer and cirrhosis. Photoresponsive chemistries allow light to be used to modulate the stiffness in these materials with high resolution. However, when creating more complex patterned gels with photomasks, bulk property analysis cannot capture the variation. To circumvent this and measure the stiffness of these complex gels, I performed rheology and fluorescence recovery after photobleaching (FRAP) to establish a correlation between diffusivity and stiffness in flood-illuminated gels. By finding and using the correlation, I am able to calculate the stiffness of the more complex patterned gels based off of their FRAP-derived diffusivity measurements. This method allows for better fine tuning of gels for use as a platform to study human cell growth through a range of stiffening events in multiple different parts of the body.

Hypoxic ischemic encephalopathy (HIE) is a neurological condition resulting from reduced blood and oxygen flow to the brain and is a leading cause of morbidity and mortality in neonates. Limited treatment options necessitate accessible and scalable interventions to improve outcomes in newborns impacted by HIE. Extracellular vesicles (EVs) have been previously shown to attenuate oxidative stress and inflammation in the brain. Further research suggests that EVs secreted by astrocytes, a brain cell type involved with the inflammatory and injury response, may elicit neurotrophic or neuroprotective properties. In this study, I isolated, characterized, and evaluated the therapeutic potential of astrocyte-derived EVs (AEVs) in an ex vivo model of hypoxic-ischemic (HI) brain injury. AEV characterization via protein assays and nanoparticle tracking analysis showed that we were able to produce AEV particles about 100 nm in size at concentrations up to 10^11 particles/mL. To assess their therapeutic efficacy, I administered AEVs at varying doses (5, 12.5, 25, and 50 µg) to neonatal rat brain slices exposed to oxygen-glucose deprivation (OGD), an ex vivo model for HI injury. Following 24h of exposure, I evaluated cell viability. Our results indicate that AEVs decrease cytotoxicity in a dose-dependent manner. To further elucidate AEVs’ mechanisms of action, we conjugate AEVs with quantum dots to track AEV localization and cell-type specific uptake in brain tissues. Understanding AEV interactions with neural cells provides insight into both the roles of AEVs and different brain cells in modulating inflammatory responses and promoting neuroprotection. By characterizing AEVs and their therapeutic potential, these findings contribute to the growing body of research on EV-based therapeutics and lay a foundation for developing reliable and scalable therapies with the potential to advance treatments for neurodevelopmental disorders and aid brain injury recovery.