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EXPLORING THE ANALGESIC EFFECTS OF DOPAMINE D3 RECEPTOR NEGATIVE ALLOSTERIC MODULATORS (D3R NAMS)
No full textPain management remains a critical aspect of healthcare, necessitating the constant search for novel analgesic targets and compounds. The dopamine D3 receptor has emerged as a potential player in modulating pain perception, making it an intriguing target for analgesic drug development. This study investigated the analgesic and behavioral effects of novel dopamine D3 receptor negative allosteric modulators (D3R NAMs), UNC6869, UNC8747, and UNC7108, in mice using the hot plate test and assessing locomotor activity. Male mice were administered 0, 40, and 80 mg/kg doses of these compounds using a cumulative dosing procedure. Hot plate assays were conducted to measure changes in responses to thermal stimuli (time to nocifensive behavior), and locomotor assays were performed to control for nonspecific behavioral effects. Results demonstrated a dose-dependent increase in the latency to nociceptive responses, suggesting potential analgesic effects mediated by UNC6869, UNC8747, and UNC7108. D3R NAMs did not significantly alter overall locomotor activity at analgesic doses, but potential toxicities were observed 24-48 hours later. Organ histopathology confirmed that 80 mg/kg exposure to these drugs produced acute kidney injury (AKI) along with some pathological changes in the spleen, liver, and pancreas. Overall, these studies explore the promising analgesic properties of D3R NAMs and highlight the importance of toxicology when testing a new class of compounds
IN THEIR OWN WORDS: NARRATIVES OF SECONDARY MATHEMATICS TEACHERS’ SELF-EFFICACY
No full textThe purpose of this qualitative narrative inquiry study was to explore how secondary mathematics teachers described their self-efficacy and how their early experiences, instructional practices, and professional relationships influenced their commitment to teaching. Although national efforts have focused on teacher recruitment, limited research examined how mathematics teachers develop and sustain teacher self-efficacy. Strengthening teacher self-efficacy is essential for supporting effective mathematics instruction, student learning outcomes, and sustained commitment to the profession. The study was grounded in Bandura’s (1977) theory of self-efficacy and examined the lived experiences of five secondary mathematics teachers. Data was collected through individual interviews, material culture review, and a focus group discussion. Findings revealed that teacher self-efficacy is cultivated personally and reinforced socially through collaboration, reflection, and professional support. Strengthening these conditions through mentoring, professional development, and collaboration can enhance teacher resilience and retention in mathematics education. This study contributes to understanding how secondary mathematics teachers’ stories illuminate the relationship among personal belief, instructional innovation, and long-term professional commitment
The Role of Emerin in Myogenic Differentiation
No full textThe nucleus harbors genetic material encapsulated by the nuclear envelope which is composed of an inner and outer nuclear membrane. The establishment and organization of chromatin at the INM is essential for cell fate during the differentiation program. Integral INM proteins are responsible for chromatin organization at the nuclear envelope. Emerin is a highly conserved type II integral INM protein with roles in chromatin organization, cell signaling, and nuclear structure. Mutations in the emerin gene cause Emery Dreifuss Muscular Dystrophy 1 (EDMD1). Emerin is ubiquitously expressed, but loss of emerin function affects specifically skeletal muscle and cardiac tissue. The precise mechanisms driving EDMD1 remain to be elucidated, but failure to repair skeletal muscle likely contributes to its pathogenesis. Previous work suggested emerin may participate in myogenic progenitor differentiation during skeletal muscle regeneration, but how emerin regulates myogenic differentiation remains poorly understood. In this dissertation, we identified two new emerin binding partners that likely contribute to higher order chromatin organization at the nuclear envelope. We performed a multi-omic analysis to investigate expression profiles and chromatin organization of differentiating myogenic progenitors expressing wildtype emerin, EDMD1 emerin mutations, or lacking emerin entirely to assess emerin’s role in transcriptional reprogramming. Lastly, we utilized lipid nanoparticles bearing emerin mRNA to rescue myogenic differentiation of emerin-null myogenic progenitor cells, as a proof-of-principle for a therapeutic approach
The Experiences of Women and Their Pursuit of District Leadership Positions and/or a Superintendent\u27s Position in New Jersey Public Schools
No full textColleen Cancila THE EXPERIENCES OF WOMEN AND THEIR PURSUIT OF DISTRICT LEADERSHIP POSITIONS AND/OR A SUPERINTENDENT’S POSITION IN NEW JERSEY PUBLIC SCHOOLS 2025–2026 Cecile Sam, Ph.D. Doctor of Education The aim of this study was to understand the experiences of women PreK–12 district-level leaders in New Jersey public school districts. A greater understanding of how their experiences impacted their career trajectories provides insight into the gendered nature of the superintendency and the hierarchy of leadership in New Jersey public school districts. This qualitative, heuristic phenomenological study (Moustakes, 1990) investigated the experiences of 10 district-level leaders in New Jersey public school districts. The findings illuminated the intersection of gendered expectations, emotional labor, systemic barriers, and internalized norms that shaped how participants navigated leadership. Far from being solely a pursuit of prestige or power, their advancement was often fueled by moral conviction, resilience, and a desire to enact systemic change for students, educators, and families
DECIPHERING FEUP–FEUQ SIGNALING: MECHANISTIC ANALYSIS OF A NEWLY IDENTIFIED REGULATORY MODULE IN AGROBACTERIUM TUMEFACIENS
No full textTwo-component systems (TCS) are widespread signal transduction pathways that enable bacteria to sense and respond to environmental changes with precision. TCS are fundamentally important to prokaryotes because they provide a rapid and efficient means of converting environmental stimuli into coordinated cellular responses. Unlike eukaryotes, which rely on multilayered signaling cascades and compartmentalized organelles, bacteria must interpret and react to changing conditions directly at the cell envelope. TCS allow prokaryotes to detect shifts in nutrients, osmolarity, pH, redox status, host-derived antimicrobials or competing microbes. This forces an immediate adjustment in gene expression programs to promote survival. Agrobacterium tumefaciens, a model organism for the study of natural genetic engineering and horizontal gene transfer, relies heavily on two-component regulatory systems. As such, upon discovery of a novel TCS: FeuP-FeuQ, in Agrobacterium tumefaciens, we hypothesized that this system plays a role in the regulation of cellular development. Data presented in this work suggest that FeuP-FeuQ functions as a regulatory module that links envelope or redox sensing to the coordinated control of surface attachment, motility and stress adaptation in A. tumefaciens
PARENTAL PERSPECTIVES ON PREPAREDNESS OF YOUNG ADULTS WITH INTELLECTUAL DISABILITIES FOR TRANSITION TO ADULTHOOD
No full textAbstract Oretha Bennett-Spence PARENTAL PERSPECTIVES ON PREPAREDNESS OF YOUNG ADULTS WITH INTELLECTUAL DISABILITIES FOR TRANSITION TO ADULTHOOD 2026 JoAnn Manning, Ed.D. Doctor of Education The transition from high school to adulthood presents significant challenges for young adults with intellectual disabilities and their families. Although schools are required to provide transition services, limited research has examined parents’ lived experiences navigating this process. This qualitative study explored how parents perceive their child’s preparedness for adulthood and postsecondary life. Guided by Schlossberg’s (1981) 4S Transition Framework and Interpretative Phenomenological Analysis (IPA), the study examined the experiences of six parents whose young adults were enrolled in or had recently completed a public-school transition program in New Jersey. Data were collected through semi-structured interviews, researcher journaling, and member checking. Analysis revealed themes related to adaptive skill development, post-school service gaps, emotional uncertainty, and school family collaboration. Parents emphasized the need for practical life skills instruction, community integration, and clearer pathways to employment and adult services. Findings indicate that while transition programs provide foundational supports, systemic barriers and inconsistent services continue to contribute to parental stress. Implications include strengthening school family partnerships, enhancing person-centered planning, and providing earlier, coordinated transition supports. This study highlights the importance of incorporating parent perspectives to inform transition planning for young adults with intellectual disabilities
The Interactions Between Part-Time African American Male Students And Academic Advisors In A One Stop: A Case Study
No full textThis qualitative case study examined how interactions between part-time African American male students and their advisors in a one-stop enrollment center motivated them to persist. Guided by Wood and Harris’s Socio-Ecological Outcomes (SEO) model, the study focused on the non-cognitive, academic, environmental, and campus ethos domains to explore how advising relationships support both advisors and part-time African American male student success. Data collection included observations of six advisor–advisee pairs across three campuses and interviews with both advisors and students. Stake’s (1995) approaches of direct interpretation and categorical aggregation guided the analysis. Findings indicated that academic advisors acted as validating agents, helped students navigate institutional processes and provided essential referrals related to academic advising such as attending tutoring or visiting faculty during office hours. These interactions fostered accountability, academic navigation, validation, and a sense of belonging, ultimately supporting persistence. The study revealed how interactions between academic advisors and part-time African American males motivated them to persist within a one-stop enrollment center. The results underscore the critical role of proactive and relational advising in addressing barriers faced by part-time African American male students. Implications for practice include enhancing advisor training in intrusive advising techniques, expanding cross-training within one-stop centers, and developing intentional strategies to build trust and belonging. This study contributes to the literature by shifting the narrative from deficit framing toward one that emphasizes resilience, agency, and the importance of meaningful advising relationships to support the success of both advisors and part-time African American male students
TUNABLE 3D-PRINTED BIOMATERIALS FOR PERFUSED IN VITRO MODELS OF THE BLOOD-BRAIN BARRIER
No full textIn vitro models have tremendous utility for improving our understanding of complex physiological and pathophysiological processes in a more controlled environment than animal models, in addition to incorporating human cells to overcome species-specific disparities. This dissertation describes innovations in biomaterial-based fabrication processes that advance in vitro models of the blood-brain barrier, providing the opportunity to evaluate the effects of cell-matrix interactions on barrier integrity, additives to reduce viscous drag of blood flow, and molecular mechanisms underlying the cellular response to amyloid beta in the context of Alzheimer’s disease. The core technology underlying this advance is a biomaterial compatible with digital light processing that yields spatial control of tunable, bioactive peptide motifs. The biomaterial can be 3D-printed into hydrogels with complex and interpenetrating topologies with peptides linked both to the lining and within the bulk of the material. Section 1 of the results details experiments interrogating the effect of peptide motifs on blood-brain barrier integrity. Section 2 focuses on using the 3D model as a testbed to evaluate drag-reducing polymers and the interaction between the endothelium and whole blood. Section 3 involves the incorporation of amyloid beta peptides and their effect on gene expression of induced pluripotent stem cell-derived endothelium. Additionally, this dissertation also describes commercialization of this technology for the perfusion of vascularized organoids
MSCL-X: Meta Supervised Contrastive Learning with Gaussian Prototypes For Robust Few-Shot Open-Set Modulation Classification
No full textAutomatic modulation recognition has found its way into the core modern-day wireless communication systems whereby intelligent receivers estimate signal formats without any prior coordination with the transmitters. Challenging situations arise in any working radio frequency environment for the conventional modulation recognition systems due to insufficient labeled data, rapidly fluctuating channel conditions, and appearance of plenty other unseen modulation types. Taken together, these challenges raise questions concerning the ability to institute learning frameworks that could perform well on few-shot and open-set conditions. Hence the thesis attempts to address the same by proposing two complementary learning-based frameworks for few-shot open-set modulation recognition by using signal constellation representation, meta-learning, and contrastive learning methods.The first chapter provides a few-shot open-set automatic modulation classification frame- work based on meta-learning and signal constellation diagrams. The complex IQ samples are transformed into a constellation image and are processed through an encoder based on ResNet18 in an episodic meta-learning framework. The strategy employs a prototype-guided learning approach to enable rapid adaptation from a small set of labeled samples, while an uncertainty-aware open-set loss has been integrated into the framework to alleviate overconfident predictions on unseen modulation types. The proposed technique is trained for 30,000 episodes of meta-learning over 48 modulation classes and multiple signal-to-noise ratio conditions, ensuring stable convergence, strong prototype formation, and reliable rejection of unknown signals. Experimental results prove that the framework maintains a balance between classification accuracy and open-set awareness, making it suitable for dynamic spectrum environments. The second part of the thesis is dedicated to developing a Meta Supervised Contrastive Learning framework (MSCL-X) for further improving few-shot open-set modulation recognition. Rather than relying upon the traditional supervised classification schemes, MSCL-X learns a discriminative embedding space applying supervised contrastive learning to constellation images derived from raw IQ samples. This encourages strong intra-class compactness and large inter-class separation in the feature space. Gaussian prototypes are fitted to the embeddings learned from known modulation classes enabling likelihood-based classification and principled rejection of unknown signals. Extensive experimental evaluations under realistic channel impairments show that MSCL-X consistently outperforms state-of-the-art open-set baselines such as OpenMax-Lite, ICS-Lite, and GE2E-Lite regarding macro-F1 score and normalized accuracy. To conclude, this thesis demonstrates combining constellation-diagram representations with meta-learning and supervised contrastive learning as a powerful, data-efficient method of few-shot open-set modulation recognition. The proposed frameworks attain robustness to channel perturbations, reduce dependency on large labeled datasets, and achieve reliable detection of unfamiliar modulation types. These contributions push intelligent wireless signal recognition further along its SOTA and provide practical value for cognitive radio, spectrum monitoring, and electronic warfare applications in dynamic and non-cooperative environments
Reconstructing Soil Conductivity Profiles from Electromagnetic Induction Data
No full textConstruction of infrastructure in cold regions poses a significant challenge, particularly due to permafrost degradation, which can lead to significant structural damage and deterioration to facilities and transportation systems. In recent years, the issue of geophysical hazard detection has been instrumental in minimizing ground subsidence risks when con- structing infrastructure in cold regions. As a commonly used technology for geophysical applications, electromagnetic induction (EMI) can be used for (i) detecting ground subsurface layers and (ii) characterizing soil types via electrical conductivities. However, EMI technology tends to struggle with lower resolution at lower frequencies and shallow depth of penetration at higher frequencies. Utilizing multi-frequency EMI (MFEMI) sensors is one way to minimize both issues. This thesis addresses the inverse problem of reconstructing the one-dimensional (1-D) electrical conductivity profile of a horizontally layered earth from data measured by an MFEMI sensor. To solve this inverse problem, a least-squares method was used. This method determines the conductivity profile by minimizing the square error between the magnetic field data collected by the MFEMI sensor and simulated data generated by a 1-D forward model. Several techniques for enhancing the stability of the inversion algorithm are presented. Inversion results from simulated datasets demonstrate that the proposed algorithms were able to reconstruct soil conductivity profiles with high accuracy for synthetic data