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Black EpiSTEMologies: Advancing Racial Equity for Black Students in STEM
No full textIn the current climate of increasing anti-Diversity, Equity, and Inclusion (DEI) policies, the educational landscape for Black students, particularly in STEM fields, faces significant threats. This research, grounded in qualitative data from focus groups with 75 Black undergraduate STEM students provides insights into how Black students persist despite systemic barriers within STEM spaces. To analyze the experiences of Black undergraduate STEM students, we employed a latent, inductive thematic analysis to uncover systemic barriers embedded in their narratives. Grounded in a theoretical framework that centers Black epistemologies, Intersectionality, BlackCrit, and Afrocentric and Diasporic thinking, our work challenges reductive approaches to understanding Black student experiences. These frameworks affirm the value of Black ways of knowing and being, providing a foundation for addressing systemic inequities and fostering the imagination, ingenuity, and inspired inquiry needed in Black education spaces. Our findings reveal that Black students navigate oppressive policies by drawing strength from critical support networks, a sense of belonging, family, purpose, and faith. These factors serve as counter-narratives to deficit-oriented discourses, highlighting the resilience and agency of Black students in STEM. Using our theoretical framework, we interpret these findings to emphasize the importance of creating Black Education Spaces that affirm Black identities and provide the cultural, emotional, and intellectual support necessary for Black students to thrive. This study not only informs our understanding of Black STEM students’ persistence but also guides the development of strategies to support Black students in K-12 and beyond.https://digital.library.ncat.edu/honorscollegesymposium25/1004/thumbnail.jp
New Farmers of America Association
No full textParade with floats pulled by mules in front of Carnegie Hall Library at Tuskegee Institute, Tuskegee, Alabama. (now Tuskegee University)https://digital.library.ncat.edu/photos/2023/thumbnail.jp
Development and characterization of plant-based surimi: A sustainable protein source for next-generation seafood
No full textThe growing demand for sustainable protein sources has led to advancements in plant-based seafood alternatives, particularly surimi. This study developed and characterized plant-based surimi (PBS) using soy, pea, and mung bean protein isolates combined with konjac glucomannan and oleogel. Seven formulations were analyzed for their physicochemical, textural, rheological, and morphological properties. Pea protein-based surimi (PBS2) exhibited the highest hardness (3781.11 g) and chewiness (2106.37 g), attributed to its compact microstructure and strong gel network. In contrast, PBS6 (mung bean and pea protein) had the lowest hardness (1319.60 g) and chewiness (564.82 g), indicating weak protein cross-linking and an unstable gel structure. Differential scanning calorimetry showed that PBS7 (soy-pea-mung bean blend) had the highest thermal stability (denaturation at 150.56°C), suggesting enhanced protein interactions and gelation properties. Scanning electron microscopy revealed significant microstructural variations, with PBS2 forming a compact fibrous network similar to traditional fish-based surimi, whereas mung bean-based formulations displayed porous, discontinuous matrices. The findings highlight the impact of protein selection and blending strategies on PBS functionality. This study demonstrates that optimizing protein composition and processing conditions can lead to high-quality plant- based surimi, offering manufacturers a viable alternative to conventional seafood product.https://digital.library.ncat.edu/gradresearchsymposium25/1132/thumbnail.jp
A Microphysiological Model for Investigating Aβ-Induced Microvascular Dysfunction and Immunotherapeutic Impact
No full textAnti-amyloid immunotherapies represent a promising avenue for Alzheimer’s disease (AD) treatment by targeting amyloid-beta (Aβ); however, their administration is associated with adverse cerebrovascular effects, including ARIA-E/H (edema/hemorrhage) and Cerebral Amyloid Angiopathy (CAA). Despite growing evidence implicating Aβ in microvascular pathology, the mechanisms governing its impact on the neurovascular unit remain unknown. This study employs a microfluidic-based Familial Alzheimer’s Disease-Brain Microphysiological System (FAD- BMPS) to elucidate Aβ-mediated blood-brain barrier (BBB) disruption, vascular amyloid deposition, and inflammatory cascades. Our findings indicate that Aβ compromises endothelial integrity by destabilizing tight junctions, increasing BBB permeability. While promoting the secretion of tight junction and adhesion proteins. Elevated Aβ concentrations correlate with an upregulation of pro-inflammatory cytokines and chemokines, including, TNF-α, and MMP-9. To further investigate the therapeutic implications, this model will assess the impact of inflammatory function on BBB stability and ARIA-related pathologies. We propose that such interventions modulate endothelial function, exacerbating vascular permeability and inflammatory responses, ultimately contributing to ARIA pathogenesis. The FAD-BMPS offers a platform for dissecting Aβ-induced vascular pathology and evaluating therapeutic interventions, granting mechanistic insights into CAA and ARIA.https://digital.library.ncat.edu/gradresearchsymposium25/1135/thumbnail.jp
Identification of Allergenic Peanut Protein and Peptides Resistant to Alcalase Hydrolysis
No full textPeanut allergy is one of most severe and persistent food allergies. While Alcalase hydrolysis significantly reduces major allergenic proteins, residual allergenicity remains a concern. This study aimed to identify resistant proteins/peptides contributing to the allergenicity of extensively hydrolyzed peanut protein concentrate (PPC). Peanut protein concentrate (PPC) at concentration of 10% was hydrolyzed with 4% Alcalase for 2-8 hours. The degree of hydrolysis (DH) increased from 34.91% to 44.68% accompanied with decreased IgE-binding. However, the SDS-PAGE and Western blot of both supernatants and precipitates with pooled sera from 7 peanut sensitive patients confirmed the presence of resistant allergenic peptides in the extensively hydrolyzed PPC, particularly, the two proteins/peptides with molecular weights 22.5kDa and 12.65kDa. To further characterize these resistant proteins/peptides, gel samples of these two peptides were sent a commercial service lab for sequencing using liquid chromatography-mass spectrometry (LC-MS/MS). The sequences obtained do not match any sequences of the native proteins in the PPC. This suggests that they are the peptides formed during Alcalase hydrolysis of larger proteins. Findings indicate that Alcalase hydrolysis alone is insufficient to eliminate peanut allergenicity. Further strategies are necessary to break down or mask all immunoreactive epitopes, enhancing the safety of peanut-based products.https://digital.library.ncat.edu/gradresearchsymposium25/1139/thumbnail.jp
Improving OER Performance of NiRu Layered Double Hydroxide: Including Influence of Reaction Time on Morphology and Electrochemical Activity
No full textIn this study, NiRu layered double hydroxide (LDH) was synthesized using the Precipitation method for oxygen evolution reaction (OER). The synthesis was carried out at a constant temperature of 80°C, while the reaction time was varied (2 hours, 3 hours, and 4 hours) to investigate its effect on the catalyst\u27s morphology and electrochemical performance. Scanning electron microscopy (SEM) analysis confirmed a well-defined morphology, with improvements observed as the reaction time increased. Electrochemical evaluation revealed that the over potential values for the samples synthesized at 2, 3, and 4 hours were 294 mV, 144 mV, and 144 mV, respectively. Compared to previously reported Ni-based LDH catalysts, the NiRu-LDH synthesized in this study exhibits superior performance, with a significantly lower overpotential and higher current density, making it a strong candidate for practical OER applications. Additionally, the current density of the catalyst exhibited an increasing trend with longer reaction times, indicating enhanced catalytic activity. Characterization techniques conducted in this study , including X-ray diffraction (XRD),Fourier-transform infrared spectroscopy (FTIR), cyclic voltammetry (CV), linear sweep voltammetry (LSV), and SEM and the findings highlight the impact of reaction time on the performance of NiRu LDH and its potential as an efficient catalyst for OER applications.https://digital.library.ncat.edu/gradresearchsymposium25/1143/thumbnail.jp
Integrating Personalized Incentives for Enhanced Transportation System Management
No full textAs the issue of urbanization accelerates, transportation networks face growing congestion challenges, leading to increased travel delays, environmental impacts, and infrastructure strain. Traditional Transportation System Management (TSM) strategies focus on optimizing traffic flow and enhancing infrastructure efficiency, but demand-side approaches—such as behavior incentives—offer promising alternatives. This research explores the integration of personalized incentives (such as monetary rewards, tokens, and gamification) within TSM to encourage off-peak travel and multimodal transportation choices. Preliminary hypotheses suggest that tailored incentives will significantly improve compliance and reduce peak-hour congestion. Furthermore, we hypothesize that integrating dynamic, user-specific incentives with an existing multimodal trip planner can significantly improve traffic distribution. To test this, we are designing behavioral experiments and developing simulation models to assess user responses. The experiments take into consideration both rational and non- rational user behaviors in decision making. Additionally, we present a survey of existing congestion mitigation strategies to inform our approach. The findings aim to inform the development of adaptive, user-centered solutions for reducing urban congestion while enhancing mobility and sustainability.https://digital.library.ncat.edu/gradresearchsymposium25/1165/thumbnail.jp
Investigating the capability YOLOv8 object detection framework employing deep learning and machine learning algorithms, to accurately identify objects
No full textThe rapid advancements in artificial intelligence (AI), coupled with the proliferation of the Internet and the Internet of Things (IoT), are transforming the application of AI technologies, particularly in object detection. This research explores the feasibility of using a standard laptop webcam as an input source for real-time object detection. Specifically, it investigates the capability of You Only Look Once version 8 (YOLOv8), a state-of-the-art object detection framework employing deep learning and machine learning algorithms, to accurately identify objects (e.g., weapons) from webcam input. This work establishes a baseline model for object detection using deep convolutional neural networks, aiming to inform future research, development, and training, especially for users with limited technical expertise.https://digital.library.ncat.edu/gradresearchsymposium25/1168/thumbnail.jp
Integrating in-vitro neurovascular organoids and computational models for understanding Alzheimer\u27s disease onset mechanism and progression
No full textAlzheimer’s disease (AD), known as the leading cause of dementia, currently lacks an early detection procedure and treatment. One in three older Americans die with AD dementia; 6.9million Americans aged 65 and older are living with Alzheimer\u27s dementia. This number is projected to double by 2060, including younger-onset dementia leading to AD. This research proposal seeks to provide answers to: What is the role of neuronal electrical circuits and activities in the onset and progression of AD? We hypothesize that oxidative stress initiates and accelerates AD, with the objective of developing a multidisciplinary platform that facilitates decoding the interaction of neurodegenerative-oxidative biomarkers in AD model; utilizing induced pluripotent stem cell techniques to develop in-vitro 3D mini brain organs in the form of neurovascular organoid models, and high-density microelectrode arrays to measure electrophysiological biomarkers of the developed models in real-time for understanding and tracking the AD progression. We will conduct assays for oxidative stress biomarkers (glutathione, superoxide dismutase, among others), integrating machine learning algorithms and HDF5 data format to analyze large datasets from our experimental procedures. Finally, we will evaluate the specificity and sensitivity (validation/correlation) of our findings for early diagnosis and therapeutic purposes in relation to AD unraveling.https://digital.library.ncat.edu/gradresearchsymposium25/1177/thumbnail.jp
Cell-Free Engineering of Synthetic Phages to Overcome Pseudomonas Aeruginosa Resistance
No full textMultidrug-resistant Pseudomonas aeruginosa is a major global health threat, demanding innovative therapeutic solutions beyond traditional antibiotics. Bacteriophages, viruses that infect bacteria, offer a promising alternative. Traditional phage engineering approaches rely on bacterial hosts for genome replication, mutation screening, and functional validation, leading to longer experimental timelines, unpredictable recombination events, and host dependent constraints. To overcome these limitations, we present a novel approach to rationally design and construct synthetic phages with reduced genomes to evade bacterial defense mechanisms. Starting from a de novo synthesized wild-type phage genome, we systematically eliminate nonessential regions while integrating targeted mutations to bypass bacterial resistance, including CRISPR-Cas and restriction-modification barriers. Unlike conventional approaches, our method employs a cell-free transcription translation (TXTL) system for rapid genome prototyping, precise modifications, and predictable engineering. This approach eliminates the host constraints by in vitro phage genome assembly and functional validation, facilitating iterative design and precise genetic modifications before host introduction. Our method improves precision, efficiency, and reproducibility in phage engineering by overcoming bacterial propagation constraints and establishing a next generation framework for targeted phage therapies.https://digital.library.ncat.edu/gradresearchsymposium25/1186/thumbnail.jp