Objectives/Goals: Osteoarthritis (OA) is a multifactorial disease where sustained gut inflammation is a continued source of inflammatory mediators driving degenerative processes in joints. The goal was to use spontaneous equine model to compare fecal and leukocyte microbiome and correlation to transcriptome in OA. Methods/Study Population: Seventy-six horses (31 OA, 45 controls) were enrolled by population-based sampling. Feces and peripheral blood mononuclear cells (PBMC) were collected. Horses were determined to have OA by clinical and radiographic evidence. Horses were excluded if they received medications or joint injections within two months. Fecal and circulating leukocyte bacterial microbial 16s-seq was performed. Bulk RNAseq of PBMC was performed by the Illumina platform. Gene expression data were mapped to the equine genome, and differential expression analysis was performed with DESeq2. Qiime2 was used for microbial analysis. Enrichment analysis was performed with a cluster profiler. Correlation analyses were performed between the datasets. Results/Anticipated Results: Beta and alpha microbial diversity differed in feces and PBMC of OA vs. healthy horses. Horses with OA had an increased Firmicutes to Bacteroidetes ratio compared with controls. The fecal microbiome of OA horses had significantly higher amounts of Firmicutes Oribacterium (q Discussion/Significance of Impact: These data suggest that altered microbiome and PBMC gene expression are associated with naturally occurring OA in the translational equine model. While Oribacterium has been detected in humans with rheumatoid arthritis, its role in OA warrants further proteomic and metabolomic profiling.

Objectives/Goals: Identify risks in the regulatory reliance ecosystem, specifically for generic reliance pathways, using system theoretic process analysis (STPA), a proactive hazard analysis method, and create sustainable solutions to ensure global accessibility to the highest attainable standard of health. Methods/Study Population: A systematic literature review will assess the regulatory reliance ecosystem and interactions among National Regulatory Agencies (NRAs). This will involve using a hierarchical control structure (HCS) to identify operational loop failures, decision-making, and information flow. The HCS will inform an STPA to prevent adverse outcomes like patient harm or regulatory non-compliance. With IRB approval, 10 regulatory experts will also be interviewed to gather insights on risk scenarios. Their input will be used to integrate regulatory pathways into the HCS for adaptability, and a second round of interviews will be conducted to validate the scenarios and assess the effectiveness of recommendations. Results/Anticipated Results: A preliminary literature review on regulatory reliance pathways from PubMed, WHO guidelines, and the DIA global forum, revealed potential risks in NRA interactions, such as overly redacted reports obscuring critical details and discrepancies in product versions or incomplete reviews affecting evaluations. Diverging guidelines and failure to adapt to country-specific needs are potential risks that also impact patient access to essential medicines. The STPA framework, along with expert feedback, will uncover unknown risks like “secondary-reliance” and soft risks, leading to sustainable recommendations to improve and optimize the safety of regulatory reliance. Discussion/Significance of Impact: Safe regulatory reliance is crucial for global health equity and patient access to essential and innovative medicines. STPA will identify and address different layers of risk in the system, improving safety, efficiency, and innovation for timely patient access to therapeutics.

Objectives/Goals: To design a flexible, comprehensive framework for Data Science Units to cultivate sustainable, long-term relationships with Clinical and Translational Science Research Units. Best practices for managing Data Science collaborations are presented to improve the quality and efficiency of research conducted throughout academic health centers. Methods/Study Population: Leaders of Data Science Units across six institutions formed a workgroup to develop guidance and best practices for Data Science Units to establish long-term, sustainable collaborations with Clinical and Translational Science Research Units. This guidance is based on tools and protocols developed and employed by the participating units, which range from larger groups with over 20 partnerships to a unit with three partnerships that is actively working to expand. Importantly, partnerships are highly variable, with some partnerships at one institution representing engagement with over 500 faculty, whereas some partnerships at another institution involve the lab of a single investigator. Results/Anticipated Results: We offer guidance in three domains: (1) Identifying the needs for a new partnership, including assessing required effort and data science expertise, setting partnership priorities, developing formal agreements, and identifying goals and metrics; (2) managing data science teams by implementing regular meetings, creating project intake and prioritization processes, and effort monitoring; and (3) evaluating the successes and failures/gaps of the collaboration by measuring the metrics mapped to the goals. For each domain, we provide specific suggestions on which parties should be involved and how frequently the processes should occur. This guidance is applicable both to larger collaborative partnerships and to smaller, single faculty or staff partnerships, whether they are new or well-established. Discussion/Significance of Impact: Effective collaboration between data scientists and clinical and translational investigators is key to advancing data-driven research. The guidance and resources are presented to support Data Science Units in successfully managing long-term collaborations through goal-development, evaluation, and adapting to evolving research needs.

Objectives/Goals: • To determine the impact of liraglutide on inflammation and organ injury during sepsis. • To investigate the protective effects of liraglutide on microvascular dysfunction in a clinically relevant model of sepsis. • To provide evidence for the potential therapeutic use of GLP-1 receptor agonists in endothelial dysfunction in sepsis. Methods/Study Population: Sepsis was induced in mice (N = 34) by intraperitoneal injection of cecal contents (1.8 mg/g body weight) and 24-hour hyperoxia (FiO2 90–95%). Mice received saline or liraglutide (0.1 mg/kg) at 6 and 18 hours post-injection and fluids and antibiotics at 12 hours. At 24 hours, mice were euthanized for plasma, bronchoalveolar lavage (BAL), and tissue collection. Plasma inflammatory markers, organ injury markers, and BAL components were measured. In vitro, primary human lung microvascular endothelial cells (HLMVECs) were treated with saline or liraglutide for 24 hours before exposure to saline or LPS (100 ng/mL). HLMVEC barrier dysfunction was evaluated using express permeability testing (XPerT) and electric cell-substrate impedance sensing (ECIS) to measure transendothelial electrical resistance (TER). Results/Anticipated Results: In murine sepsis, illness severity scores and lung injury were improved in mice pretreated with liraglutide (N = 10). Plasma blood urea nitrogen (BUN; P = 0.0036), alanine transaminase (ALT; P = 0.0311) and vascular inflammatory markers MCP-1 (P = 0.0172), ICAM-1 (P = 0.0356), and Pecam-1 (P = 0.0493) in plasma were reduced in mice treated with liraglutide. In HLMVECs, liraglutide (1.5 nM) significantly reduced LPS-induced barrier dysfunction measured by XPerT assay (P = 0.0030) and ECIS (P = 0.0075). Discussion/Significance of Impact: Liraglutide reduces illness severity, vascular inflammation, and organ injury in a two-hit model of sepsis. Liraglutide has direct effects in the microvascular endothelium, limiting LPS-mediated barrier dysfunction. These findings support a protective role for GLP-1 receptor agonism in sepsis, mediated through the microvasculature.

Objectives/Goals: Collaborations between translational science programs and academic health sciences libraries can enhance research impact by improving efficiency, leveraging diverse professional expertise, and expanding opportunities for collaboration between librarians and translational science programs. Methods/Study Population: A team science approach was utilized, integrating findings from a literature review, practical experiences of health sciences librarians, and collaborative writing. An analysis of case studies from institutions with successful partnerships explored the roles of libraries in partnering with translational science programs. The data collected were mapped to the Clinical and Translational Science Award Program’s five functional areas outlined in the Notice of Funding Opportunity PAR-24–272. Librarians from 21 institutions engaged in discussions and collaborative writing to share insights and identify key factors driving successful partnerships. Results/Anticipated Results: Academic health sciences libraries play a crucial role in enhancing translational science programs through expert knowledge management, facilitation of research dissemination, and support for interdisciplinary collaboration. Results from this project include a table outlining 16 specific opportunities mapped across five functional areas and six topical categories for translational science programs and libraries to collaborate effectively.Successful partnerships demonstrate improved research workflows, increased interactions between researchers and libraries, and accelerated translation of discoveries into clinical settings. These collaborations illustrate opportunities for other institutions to adopt as they consider best practices in supporting translational science. Discussion/Significance of Impact: By combining resources and expertise between libraries and translational science programs, these partnerships enhance the ability to transform scientific discoveries into real-world clinical applications, drive innovation, and amplify the contributions of both libraries and translational science programs.

Objectives/Goals: Lung transplant is a life-saving surgery for patients with advanced lung diseases yet long-term survival remains poor. The clinical features and lung injury patterns of lung transplant recipients who die early versus those who survive longer term remain undefined. Here, we use cell-free DNA and rejection parameters to help elucidate this further. Methods/Study Population: Lung transplant candidacy prioritizes patients who have a high mortality risk within 2 years and will likely survive beyond 5 years. We stratified patients who died within 2 years of transplant as early death (n = 50) and those who survived past 5 years as long-term survivors (n = 53). Lung transplant recipients had serial blood collected as part of two prospective cohort studies. Cell-free DNA (cfDNA) was quantified using relative (% donor-derived cfDNA {%ddcfDNA}) and absolute (nuclear-derived {n-cfDNA}, mitochondrial-derived {mt-cfDNA}) measurements. As part of routine posttransplant clinical care, all patients underwent pulmonary function testing (PFT), surveillance bronchoscopy with bronchoalveolar lavage (BAL), transbronchial biopsy (TBBx), and donor-specific antibody testing (DSA). Results/Anticipated Results: Over the first 2 years after transplant, the number of episodes of antibody-mediated rejection (p) Discussion/Significance of Impact: Clinically, early-death patients perform worse on routine surveillance PFTs and experience a worse degree of CLAD. These patients also have higher levels of cfDNA as quantified by n-cfDNA and mt-cfDNA. These results provide preliminary evidence that early-death patients have worse allograft rejection, dysfunction, and molecular injury.

Objectives/Goals: Aims are to identify the gaps and discrepancies between cancer care teams at Princess Margaret (PM) and primary care providers (PCPs). To ensure the transition from hospital care at PM into the community integrates the expressed needs of PCPs and cancer specialists. To ensure PCPs have the necessary resources to provide high-quality care to patients. Methods/Study Population: Phase 1 is the preparation phase, which consists of searching the literature and conducting contextual inquiry with experts in relevant fields, such as cancer survivorship and primary care. This phase is crucial to the planning of this project as the information gathered will be used to define the problem space and outline the scope of the project. Next (phases 2 and 3) we aim to create and distribute surveys to PCPs to gather data on current protocols and resources. We plan to distribute this survey by emailing PCPs and accessing PCP networks. Upon completion of the survey, we will review the data and assess which areas need further investigation. Then, we will create an interview guide keeping in mind the areas that need to be supplemented and aiming to validate the need. Results/Anticipated Results: A resource that presents guidelines for PCPs to assist in them taking on follow-up care responsibilities for low-risk cancer survivorship patients. These guidelines may include information such as communication pathways between PCPs and the PM Cancer Care team, expected follow-up care measures, and timeframes for follow-up care. The development of this guideline will assist in alleviating the burden on the PM Cancer Centre system as it will facilitate low-risk patients transitioning back to family care. Discussion/Significance of Impact: There is an increasing demand for oncology services post-cancer treatment at the PM Cancer Centre and the current cancer model follow-up care is not sustainable by oncologists alone. There is a need to explore innovative personalized pathways to follow-up care based on an individual’s needs and integrate family doctors.

Objectives/Goals: Idiopathic inflammatory myopathies (IIMs) are autoimmune diseases influenced by genetic and environmental factors. This study aims to explore infection patterns preceding IIM onset by applying temporal data mining and machine learning to deidentified patient records and corroborate results from molecular analysis. Methods/Study Population: The dataset used in this work was extracted from TriNetX with a focus on patients who have IIM. Risks for developing the outcomes were assessed using case–control cohorts. For each participant, information was extracted about diagnosis code, date of infection, and study visit in which the infection was reported. This data were then temporally encoded and used to generate sequence files for each of the outcomes. Unsupervised temporal machine learning was then preformed on these files to detect frequent subsequences of infections. Python library scikit-learn was used to perform the unsupervised machine learning with k-means clustering. Results/Anticipated Results: The results of this study identify infections associated with the onset of IIM by analyzing temporal infection patterns. Frequent sequences of infections uncovered, with specific patterns linked to different cohorts, offer insights into the etiology of IIM. Common and cohort-specific infection sequences will help validate existing research and provide new avenues for exploring the disease mechanisms. The findings will highlight significant infection patterns, which will inform our understanding of IIM onset across various patient populations. Discussion/Significance of Impact: The results will provide key insights into pre-symptomatic infection sequences related to IIM onset, enhancing understanding of its etiology and pathogenesis. These findings may aid in developing more precise screening methods for early detection and confirm previous results from analyzing immune signatures of infections in IIM.

Objectives/Goals: Community engagement is critical to promoting equity for those affected by clinical and translational research. Despite its importance, investigators rarely involve community stakeholders in ancillary projects such as secondary analyses. I use a study example to demonstrate how to meaningfully partner with communities in ancillary research. Methods/Study Population: Using data collected in a previous study, the aim of this secondary analysis was to examine whether pregnant women’s reports of social adversity during the third trimester were associated with their infant’s resting cortisol level at 1, 6, and 12 months of age. Community engagement at the study design phase included consultation with an institutional Community Advisory Board (CAB) whose expertise included lived experiences relevant to the context of the study (i.e., social adversity and pregnancy). Community engagement at the analysis and dissemination stage included deeper collaboration with three community research consultants (CRCs) from the CAB; all identified as women of color and mothers with relevant lived experiences. CRCs received compensation for time and effort and an invitation for co-authorship. Results/Anticipated Results: Consultations included written review as well as a live presentation and discussion with the CAB for feedback on the study proposal prior to submission for IRB approval. The focus of discussion was around the use of inclusive terminology and ensuring respectful and equitable representation of all participants in the original study, including those who reported experiences with social adversity during pregnancy. After receiving study approval, statistical analyses were finalized and CRCs actively engaged in discussions with the PI around the interpretation of results. CRCs significantly contributed to the development of solutions-oriented implications for practice, policy, and future research. All CRCs were co-authors on the study manuscript that was published in a top-tier international journal. Discussion/Significance of Impact: Community engagement in ancillary research is feasible and essential. True equitable collaboration requires partnership during all study activities, including critical phases (e.g., developing aims, data analysis). Researchers also should prioritize the use of datasets from studies that incorporated community partnership and engagement.

Objectives/Goals: Objectives/Goals (300 characters): Sarcopenia is a progressive skeletal muscle disorder associated with adverse outcomes. There is a gab of having objective measures upon performing interventions in patients with muscular dystrophies. The object of the present study is to describe the severity of sarcopenia in DMD patients in Puerto Rico. Methods/Study Population: Methods/Study Population (700 characters): Forty to 30 patients with DMD who are followed in MDA Care Center in the “Instituto De Rehabilitacion del Caribe.” Diagnosis will be confirmed with genetic testing and/or muscle biopsy. Lean muscle mass will be measured with a Whole Body Dexa (WBD) in a Nuclear Medicine Lab. Hand grip, elbow flexor, and knee extensor muscles strength will be measures with an isometric dynamometer. Patients’ functionality will done using the North Star Ambulatory Assessment scale and Brook and Vignos scales, which have been validated for patients with DMD and neuromuscular disease respectively. Correlations will be made with lean body mass (independent variable) and muscle strength and functionality (dependent variable). Results/Anticipated Results: Results/Anticipated Results (700 characters): We expect to find severe sarcopenia in patients with DMD in PR and that it will be more severe with older age. There will be a direct correlation between lean muscle mass and muscle strength, and functionality in DMD patients. Discussion/Significance of Impact: Discussion/Significance of Impact (300 characters): The findings of our study can help us to explore the possibility that Whole Body DEXA can serve as a potential biomarker for future studies since there is a need to develop noninvasive biomarkers that correlate with disease progression and interventions in DMD patients.

Objectives/Goals: This project (1) assesses provider behavior at the Galveston Secure Against the Fentanyl Epidemic (G-SAFE) Clinic in providing evidence-based care for underserved patients in our community and (2) implements evidence-based anti-stigma intervention in local health care. Methods/Study Population: The efficacy and impact of G-SAFE on healthcare utilization, health outcomes, and patient satisfaction will be determined. Evaluations assessing provider behavior will be made across at least 25 clinic patient visits, taking note of medical students, clinicians, and health providers’ interactions with patients related to decision-making, care plan creation, and communication. Health provider discussion groups will provide essential data in understanding the successful management of SUDs, management of safety and risk, and how best to pilot and assess interventions that promote greater trust-building and a harm-reduction approach to clinical care for patient empowerment and positive outcomes. Results/Anticipated Results: Observations in the clinic will be turned into interventions to improve diagnostics and therapeutics for SUD medical care and behavioral change. We will recruit 40 medical students (with/without exposure to UTMB’s free clinics) as well as 20 clinicians in the G-SAFE Clinic, Emergency Medicine, and Primary Care. Baseline stigma will be measured with the Medical Condition Regard Scale and the Drug and Drug Problems Questionnaire alongside measures of care approaches. The data collected and the educational intervention for medical students and clinicians will make a positive impact on the lives of those affected by SUDs and serve as a model for future interventions on a larger scale. Discussion/Significance of Impact: Health provider’s SUDs stigma undermines both care quality, patient empowerment, and recovery success. Addressing provider stigma is crucial for necessitating a shift toward collaborative, responsive, and creative clinical decision-making to tackle the ethical challenges posed by the opioid crisis.

Objectives/Goals: Baseline lung allograft dysfunction (BLAD) is defined as the failure to attain normal lung function after transplant and has been associated with impaired survival. BLAD has no consensus definition and assessment of varying thresholds of abnormality may identify an impact on survival or development of chronic lung allograft dysfunction (CLAD). Methods/Study Population: This is a retrospective cohort analysis of bilateral lung transplant recipients who were transplanted between 1/1/2012 and 12/31/2022 who have complete pulmonary function data posttransplant. Thresholds of BLAD including percent predicted levels of FEV1 and FVC at 80%, 75%, 70%, 65%, and 60% were assessed. Outcomes evaluated include survival, development of CLAD, and association of key risk factors with the development of BLAD including donor, recipient, operative, and postoperative characteristics. Results/Anticipated Results: Totally, 680 bilateral lung transplant recipients were identified. Prevalence of BLAD ranged from 41.9% to 9.7% at specified thresholds. We anticipate performing survival analyses and evaluating development of CLAD in patients with BLAD at varying thresholds. We are assessing key donor, recipient, operative, and postoperative variables for association with BLAD. Preliminary analyses demonstrate significant associations of BLAD with recipient-donor height mismatch, prolonged mechanical ventilation time posttransplant, increased length of hospitalization posttransplant, the use of cardiopulmonary bypass intraoperatively and surgical allograft downsizing. Discussion/Significance of Impact: A threshold of BLAD at 70% predicted FEV1 and FVC or lower suggests importance for developing CLAD. Key characteristics associated with BLAD suggest importance of height mismatch, operative complexity, frailty, and severity of disease at time of transplant and immediately postoperatively.

Objectives/Goals: MyCTSC harmonizes data from many sources into one database for evaluation, marketing, and CTSC member management to address current disparate collection and siloed use of data. It simplifies report creation with real-time dashboards so administrators and leadership can view progress quickly and plan for improvements based on real-time data. Methods/Study Population: MyCTSC is built using open-source software like Python, Django, MariaDB, Bootstrap, and Chart.js, and integrates data from sources such as systems for consult requests, pilot/voucher applications, and REDCap surveys. Each data source is imported into the warehouse either automatically via API, if available, or via manual file upload. De-duplication and other data cleaning are performed as well. Customized, real-time dashboards are developed based on the needs of administrators and leadership. While MyCTSC does not have a study population, it does have the stakeholders mentioned above as well as leadership. The development timeline spans three years: initial development and data warehouse population in Year 1, data cleaning and dashboard creation in Year 2, and full rollout to all CTSC members in Year 3. Results/Anticipated Results: MyCTSC aims to create a seamless data and member management system to resolve issues stemming from multiple data sources. Demographic challenges are addressed by implementing data cleaning and consolidating duplicate identities into a single profile. The initiative will enhance stakeholder buy-in by presenting evaluation use cases that show the impacts of CTSC resources. For example, workforce development needs will be met through surveys and integration of a course catalog. MyCTSC will also facilitate targeted resource and event advertising, and support investigator outreach and collaboration by utilizing dashboards and reports. Furthermore, it will serve as the consolidated data source for all CTSC modules, promoting greater interaction and collaboration across administration and modules. Discussion/Significance of Impact: MyCTSC integrates multiple sources, consolidates identities, and simplifies reporting for outreach and collaboration. It enhances interaction with researchers and community members, advancing translational science by linking projects and publications. MyCTSC, built with open-source software, can be made available to other CTSA hubs.

Objectives/Goals: This study demonstrates the utility of the CBID biodesign process for identifying and prioritizing high-impact neurosurgical needs. The research emphasizes the process’s role in developing innovative medical technologies that align with the healthcare ecosystem’s demands and stakeholder priorities. Methods/Study Population: The CBID Spiral Innovation Model, integrating clinical, technical, business, and strategic considerations across clinical challenges in neurosurgery was employed over a 15-week period at a tertiary care center. The process involved three phases: (1) needs identification through 8 weeks of clinical immersion, (2) 7–8 weeks of stakeholder engagement via informational interviews, surveys, and conferences, and (3) iterative refinement based on evidence generation and market value. Stakeholders included over 70 clinicians (neurosurgeons, neurocritical care specialists, neurologists, etc.) across 15 institutions as well as more than 10 payers and hospital administrators. Data collection encompassed direct observation, structured interviews, and comprehensive literature review. Results/Anticipated Results: The initial list of 300+ identified neurosurgical needs was reduced to 271 after clinician and market input. High-level market and clinical evidence assessments further reduced this to 74 needs. Finally, through iterative evaluation of evidence generation, market opportunity, and stakeholder feedback, five critical unmet needs in stroke, traumatic brain injury, hydrocephalus, and epilepsy were identified for technological innovation. These needs met the criteria for clinical importance, economic viability, and market accessibility. The findings highlight the effectiveness of the biodesign process in creating a roadmap for innovation that is both clinically relevant and commercially viable. Discussion/Significance of Impact: This study underscores the effectiveness of structured need-finding and prioritization within neurosurgery. Integrating stakeholder perspectives and rigorous analysis, it provides a replicable framework for medical innovation to accelerate the development of impactful solutions across medicine.

Objectives/Goals: Physical therapy (PT) is a recognized and evidence-based component of oncology care that has been shown to benefit people with various cancers, such as breast, lung, head and neck, thyroid, or prostate cancer. The goal of this evaluation was to determine the level of PT service utilization by World Trade Center (WTC) Health Program members with cancer. Methods/Study Population: The Program is a limited benefits federal program that serves responders and survivors of the September 11th attacks in New York City, the Pentagon, and Shanksville PA. Our analyses include enrolled Program members with a cancer certification. Cancer types were divided into two categories, Category A (breast, lung, head and neck, thyroid, or prostate cancer) and Non-Category A (all other cancer types). Data included medical claims, certification, and enrollment data from July 2011 to December 2023. The 2023 Current Procedural Terminology (CPT) code list from the Centers for Medicare and Medicaid Services were used to identify claims associated with PT interventions. Our analyses describe trends in PT claims, CPT codes, cancer certifications by subtype, and number of members with Category A cancers and PT claims. Results/Anticipated Results: Since the Program’s inception in 2011, PT claims had gradually increased except for in 2020 when there was a sudden decrease, most likely due to the interruption of in-person services due to the COVID-19 pandemic. From 2021 to 2023, PT claims began to increase again. The most common types of PT interventions were therapeutic exercises, manual therapy, and neuromuscular reeducation. In 2023, the most recent year of full data available, Category A cancers made up 38% of all cancer certifications, with prostate and breast cancer being the most common. Category A cancers were evaluated together due to prior existing evidence outlining significant benefit from PT intervention. In total, Category A cancers represent over 14,000 Program members. Less than 1% of members with a Category A cancer had a PT related claim in 2023. Discussion/Significance of Impact: The mission of the Program is to provide quality and compassionate medical care and treatment to our members. Better understanding the utilization of PT services provided by the Program will allow us to increase awareness and support of interventions for members of our Program who could benefit from PT services.

Objectives/Goals: Highlight the importance of community engagement: Showcase how the involvement of Promotoras de Salud is critical for fostering trust and encouraging participation in clinical trials. Cultural relevance and adaptation: Underline the importance of cultural and contextual relevance in developing and refining clinical research tools. Methods/Study Population: The theater test, an interactive evaluation approach akin to a dress rehearsal in theater, was conducted with approximately 60 Promotoras de Salud at a community center near the US-Mexico border. The Promotoras were divided into four groups, each focusing on one domain of the toolkit and facilitated discussions provided critical feedback on the materials and methods. A community engagement liaison with the University of New Mexico Health Sciences Center played a key role in introducing the EXPLORE team to these community leaders, leveraging long-standing relationships that predate this project. Results/Anticipated Results: Post-testing evaluations showed that 97% of the Promotoras were likely to encourage clinical trials in their communities, and 86% saw significant benefits for their community members. The Promotoras provided key insights and recommendations to enhance the toolkit’s cultural and contextual relevance. The community engagement liaison created a bilingual infographic to share these insights, which was presented at a Promotoras meeting, fostering meaningful discussion about clinical trials. Discussion/Significance of Impact: This project underscores the importance of community voices in research, transforming feedback into actionable insights for public health. Engaging Promotoras through theater testing validated the EXPLORE Toolkit and strengthened ties between clinical research and communities impacted by the opioid crisis.

Objectives/Goals: The gut microbiome and its metabolites, such as short-chain fatty acids (SCFA), are dysregulated in rheumatoid arthritis (RA); however, the significance of this observation and its implications in pathogenesis and therapeutics is unclear. Here, we explore the role of the SCFA, butyrate, in treatment efficacy in new-onset rheumatoid arthritis. Methods/Study Population: We designed a proof-of-principle study to determine the effects of butyrate supplementation in new-onset RA (NORA) patients that fulfilled 2010 ACR/EULAR RA criteria. We evaluated the effects of methotrexate (MTX) plus butyrate in NORA (n = 17; 1 gm butyrate, 3 times daily) compared to MTX alone (n = 19) over 4 months. MTX responders were defined by a change in disease activity score (DAS)-28 ESR of > 1.8 at 4 months. Fecal samples were collected at baseline and followed up for 16s rRNA sequencing and metabolite quantification by 1H NMR spectroscopy. Unpaired-t, paired-t, Wilcox and Fisher’s exact test were performed as appropriate. Results/Anticipated Results: MTX responders in the MTX-only group had a higher concentration of fecal butyrate than nonresponders at baseline (p = 0.045). Fecal butyrate concentration decreased over time in treatment responders in MTX group (p = 0.05), whereas butyrate concentration remained similar in MTX/butyrate group. Prior to treatment, both MTX and MTX/butyrate groups demonstrated similar levels of gut bacterial alpha diversity (Shannon index), yet only the MTX/butyrate group demonstrated a significant increase in alpha diversity by 4 months (p = 0.022). LefSe analysis demonstrated increased abundances of Bacteroides, Clostridium, and Phascolarctobacterium in responders in the MTX/butyrate group by 4 months. Ten (52.6%) patients in MTX and 11 (64.7%) in MTX/butyrate group were considered MTX responders by 4 months (p = 0.516). Discussion/Significance of Impact: Butyrate supplementation increased gut microbial diversity in patients and led to increased abundance of Bacteroides, which has been implicated in efficacy of methotrexate, a first line medication in rheumatoid arthritis. Butyrate may have implications for the maximization of therapeutic effectiveness in rheumatoid arthritis.

Objectives/Goals: Evaluate the impact of intrauterine growth restriction (IUGR) on neonatal brain development using magnetoencephalography (MEG) and correlate findings with NICU Network Neurobehavioral scale (NNNS) scores at 1 month Methods/Study Population: In this prospective cohort study, we will enroll 30 participants, consisting of 15 neonates diagnosed with IUGR and 15 healthy controls, matched by gestational age, from the University of Arkansas for Medical Sciences. We will perform MEG scans at three key developmental stages: during fetal life, at 1 month, and at 3 months of age and a Bayley IV exam at 12 months of age. The NNNS assessments will be conducted at the 1-month visit to evaluate neurobehavioral outcomes. All MEG data will be synchronized with clinical evaluations and maternal health records to ensure comprehensive analysis. Results/Anticipated Results: We anticipate that the study will reveal significant differences in brain maturation and neural activity patterns between IUGR-affected infants and healthy controls. Specifically, we expect to find altered neural connectivity and delayed maturation in the delta and theta frequency bands during the early neonatal period in the IUGR group. These anticipated neuroimaging findings will be correlated with NNNS scores to assess functional implications of the observed brain activity differences. If our hypotheses are confirmed, the study will provide robust biomarkers for early identification of neurodevelopmental delays in IUGR-affected infants, paving the way for targeted early interventions. Discussion/Significance of Impact: This study could significantly enhance early detection and intervention strategies for IUGR, potentially reducing long-term neurodevelopmental challenges and improving clinical outcomes

Objectives/Goals: In 2018, a novel analytic resource navigation process was developed at Duke University to connect potential collaborators, leverage resources, and foster a community of quantitative researchers and scientists. We provide information about how this process works along with guidance for academic medical centers to develop similar initiatives. Methods/Study Population: Quantitative and qualitative scientists with expertise in data science, biostatistics, epidemiology, and related fields play a critical role in data collection, study design, analysis, interpretation, and implementation. The analytic resource navigation process connects researchers with quantitative scientists and relies on strong institutional knowledge of methodological expertise, understanding of research goals, educating researchers, and ongoing evaluation to understand unmet needs. University staff serve as navigators to help researchers identify the needed expertise, find potential collaborators, and track outcomes. Duke University’s tracking system for this navigation process, implemented in 2019, underwent a nearly five-year evaluation (November 2019 – September 2024). Results/Anticipated Results: In the nearly five-year evaluation of the process, 1247 requests from 813 unique researchers were navigated with a success rate of 93.8%. A total of 323 requests (256 unique researchers) were navigated in year 1, 285 requests (239 unique researchers) in year 2, 210 requests (179 unique researchers) in year 3, and 247 requests (192 unique researchers) in year 4. In the current year (partial year 5, 11/1/2023 – 9/18/2024), 182 requests have been navigated (159 unique researchers). Unsuccessful linkages occurred in 35 requests (2.8%) and 42 requests (3.4%) were withdrawn. Among the cases of unsuccessful navigation, 26 failed due to effort (e.g., insufficient effort available to meet the researcher’s deadline), 2 failed due to lack of expertise at the institution, and 4 failed due to a lack of sufficient funding. Discussion/Significance of Impact: The navigation process provides a critical resource for researchers who need to develop collaborations and a method for institutions to understand collaboration needs. Implementation requires training knowledgeable navigators, maintaining updated information about quantitative and qualitative methodologists, and institutional support.

Objectives/Goals: The National Research Mentoring Network Coordination Center (NRMN CC) received funding from NIH to create an Online Community of Practice (OCoP) for Research Managers (RM). These RM contributed to advancing the research on the science of mentorship in STEMM. In a Proof of Concept, RM explored various aspects of their mentorship research support work. Methods/Study Population: An OCoP met 18 times across the 5-year grant to share experiences working to advance the science of mentorship in STEMM. Topics, frequency, and length of meetings were selected based upon several needs assessments surveys from the RM community. RM were invited to join the OCoP based on their roles as the point people for administrative activities in research projects (e.g., finances, budgets, training, and project management). RM often supervised staff, collected data, monitored IRB protocol compliance, and conducted research. RM played a pivotal role in the gathering and sharing of common measures across the 11 U01 studies to allow for greater confidence in research findings on mentorship (McConnell, 2021). Results/Anticipated Results: Our primary goal was to provide a supportive community for RM contributing to mentorship research and data sharing. The results from several needs assessments exemplified a request for this support from the community to engage in an OCoP focused on their professional development. Therefore, the OCoP served as a starting point to explore the duties, functions, roles and responsibilities of RM, and extended into providing professional development. Although the number of RM attending decreased as the grant entered the no-cost extension phase, a subgroup of RM expressed interest in continuing the OCoP to focus on dissemination of research findings, further supporting the need for this community. Discussion/Significance of Impact: RM supported 11 research projects and contributed to the data collection for over 6,000 participants. Few opportunities exist to create an OCoP for large scale data collection on experiences with mentorship in STEMM. RM were pivotal in their role with the NRMN to enhance the training and career development of individuals from diverse backgrounds.