Objectives/Goals: The goal of this study is to explore the lysogenized bacteriophages of clinical isolates of Pseudomonas aeruginosa (Pa) for their capacity to affect intraspecies competition. This study also aims to explore the capacity of using clinical isolates as a source of new candidates for phage therapy. Methods/Study Population: We compiled a collection of 207 Pa isolates and screened them for the presence of lysogenic phages using polymerase chain reaction (PCR). A subset of 96 phage containing clinical isolates was tested for intra-strain infectivity. Using a representative subset of isolates producing infective and non-infective phage, we evaluated competitive dynamics in liquid co-cultures, bacterial biofilms and in a murine chronic wound model. Results/Anticipated Results: Among all isolates, 74.3% contained detectable phages in their genome, and 63.7% contained detectable phage in their supernatants. Among those tested for intra-strain infectivity, 82.2% of strains demonstrated inhibition of growth on lawns of at least one other strain, while 94.8% of these strains were susceptible to at least one other supernatant. In in vitro co-culture competition experiments, strains producing infective phages outcompeted competitors more effectively than strains producing non-infective phage. Infective phage producing strains were more resistant to biofilm invasion than non-infective counterparts. In vivo competition experiments showed that PAO1 was significantly reduced when co-infecting with an infective phage-producing strain compared to a non-infective one. Discussion/Significance of Impact: Collectively, these data demonstrate that clinical isolates of Pa frequently encode active bacteriophages that can mediate intraspecies competition and confer a competitive advantage during infection. Future work will center on combining these phages as therapeutic cocktails targeting acute Pa infections.

Objectives/Goals: This work identifies ordinary and novel ingredients of a recipe for a learning community created by translational scientists to support their mutual interests in broadly engaged team science. The goal of creating this recipe is to share our findings, enabling the replication of this work at other CTSAs. Methods/Study Population: Inspired by O’Brien et al. (2025), our MICHR CoLab+ learning community (N = 8) is cooking up a “community recipe” for collaborative learning. Our multidisciplinary mix includes members from six MICHR teams. In our first guided session, we blended open dialog and reflection to identify key ingredients and tools, including metaphors for our team’s strengths, values, and goals. Using Teams, Miro, and generative AI, we captured early insights to refine over time. Results/Anticipated Results: By co-creating a community recipe, members of the MICHR CoLab+ deepen their understanding of shared strengths, values, and purpose. The recipe showcases what makes our community unique while fostering unity and belonging. Once complete, it will help us overcome barriers, accelerate discovery, and deliver real-world impact in translational science. Discussion/Significance of Impact: This work extends research helping translational scientists cross boundaries in universities. Building on work on learning communities for learning health systems (Ferguson, et al., 2024; Wenger, 1998), it shows how co-created “recipes” foster collaboration across disciplines, institutions, and cultures to strengthen translational science.

Objectives/Goals: The goal of this project was to, first, identify potential improvements to administrators’ processes surrounding the maintenance and export of a digital research platform using human-centered design and, second, explore whether this approach could be integrated into a system evaluation of implementation and impact of the platform. Methods/Study Population: In alignment with the A3 template for quality improvement, MICHR staff prepared to conduct a systems evaluation of MICHR’s support and dissemination of Your Health Research (YHR), a digital platform for study participant recruitment by (1) identifying the background of programmatic and scientific opportunities being addressed, (2) assessing the current state of MICHR’s management of YHR, and (3) identifying S.M.A.R.T. goals for improvement, as well (4) the drivers of improvement. The iterative nature of the work that was undertaken aligns with the intent of A3 framework which presents these 4 steps as an iterative process. These iterative efforts included a tabletop exercise, a blueprinting workshop, and a survey of MICHR program staff about potential improvements. Results/Anticipated Results: YHR is designed to facilitate recruitment into clinical and translational research studies; the findings presented here show that it is feasible to evaluate the way MICHR deploys this tool for increasing effect. The use of Systems Evaluation Theory was not only appropriate (Renger, et al, 2025), this work shows how human-centered design approaches can be integrated into systems evaluations to facilitate the identification and continuous improvements to those systems (Melles, et al., 2021; Holman, et al, 2019; Meyer, et al, 2022). This work shows how clinical and translational science organizations like MICHR can contribute to the emergence of learning health systems by evaluating the infrastructure of academic medical centers designed to facilitate participant recruitment into research (Lopez et al., 2025). Discussion/Significance of Impact: This study responds to an enduring need for more research into the ways research institutions like MICHR can increasingly provide investigators with better infrastructure and tools, such as access to population-based data for real-time adjustments to their clinical and translational research studies.

Objectives/Goals: To assess how rigor and reproducibility activities across the Clinical and Translational Science Awards (CTSA) consortium are aligned with NCATS Translational Science Principles (TSPs) and the NIH’s new plan to promote gold standard science. Methods/Study Population: We conducted a retrospective, descriptive review of all CTSA hub Research Performance Progress Reports (RPPRs) submitted for the most recent reporting year, focusing on the Accomplishments section. Reports were systematically searched using predefined rigor and reproducibility-related keywords. Relevant content was abstracted using a structured framework to categorize activities across domains, including education and training, institutional support, and data management and sharing. Results were summarized quantitatively by award mechanism. Results/Anticipated Results: Sixty-two of 66 CTSA institutions reported activities related to scientific rigor and reproducibility in the RPPR Accomplishments section. Among these hubs, rigor and reproducibility activities were most frequently reported under K awards (48 hubs), followed by UL2 or UM1 awards (43 hubs) and T awards (38 hubs). These findings indicate broad engagement across the CTSA consortium, with variation in how rigor and reproducibility activities are reported across award mechanisms. Discussion/Significance of Impact: Most CTSA hubs document multiple rigor and reproducibility activities as their accomplishments, reflecting alignment with NCATS TSPs. Characterizing these efforts across award mechanisms can inform strategies to strengthen translational science research that meets the NIH’s gold standard science.

Objectives/Goals: Maternal diabetes is associated with increased inflammation during pregnancy, which may elevate the risk of motor, cognitive, and language delays in their offspring. Our objective is to characterize the neurodevelopmental outcomes at 12 months of age in children born to diabetic mothers using two validated assessment tools. Methods/Study Population: We assessed 54 children across three groups: type 1 diabetes mellitus (DM) (T1DM n = 6), type 2 DM (T2DM n = 24), and control (n=24). Neurodevelopment was assessed using two standardized tools: the Ages and Stages Questionnaire 3rd edition (ASQ-3), a parent questionnaire, and the Bayley Scales of Infant and Toddler Development, 4th edition (BSID-IV). The ASQ-3 is composed of five domains: Communication, Gross Motor, Fine Motor, Problem Solving, and Personal-Social. The BSID-IV is also composed of five domains: Cognitive, Language (Receptive and Expressive), Motor (Gross and Fine), Social-Emotional, and Adaptive Behavior. For this study, we assessed only the Cognitive and Language domains of the BSID-IV. We used the Cochran–Mantel–Haenszel (CMH) Mean Scores test to compare the mean scores across the three groups. Results/Anticipated Results: The ASQ-3 showed no statistically significant differences between groups across all five domains. However, several children showed delays or were at risk for delays in multiple domains: Communication: (1 [1.85%]; 4 [16%] delayed), Gross Motor: (4 [7.4%] delayed), Fine Motor: (13 [24.1%] at risk; 7 [12.9%] delayed), Problem Solving: (9 [16.7%] at risk; 11 (20.3%) delayed, and Personal-Social: 8 [14.8%] at risk, 10 (20%) delayed). Similarly, the BSID-IV showed no statistically significant group differences in Cognition and Language. However, below-average performance was observed in both domains. For Cognition, 14 children (25.9%) scored below average (T1DM:1 [1.85%], T2DM: 7 [12.9%], Con = 6 [11.11%]). For Language, 12 children (22.22%) (T1DM = 1 [1.85%], T2DM = 4 [7.4%], and Con = 7 [12.9%]). Discussion/Significance of Impact: Children from all groups had delays in fine motor, problem-solving, personal-social, cognitive, and language development. These findings suggest that maternal diabetes may influence neurodevelopment. We suggest that these children have continued neurodevelopmental follow-up with their pediatrician to improve these delays.

Objectives/Goals: To evaluate the translational reliability, reproducibility, diagnostic performance, and subgroup equity of multimodal artificial intelligence (AI) models for dermatology triage across multiple model platforms. Methods/Study Population: Limited access to dermatology expertise delays diagnosis and care, motivating development of multimodal AI systems that integrate clinical images with patient data for triage. We assembled 200 biopsy-confirmed PAD-UFES-20 lesions (melanoma, keratinocyte carcinoma, benign) with paired images and metadata, prioritizing demographic balance. Six multimodal AI models (GPT-5, GPT-5-mini; Gemini 2.5 Pro, Gemini 2.5 Flash; Claude Sonnet-4, Claude Opus-4) analyzed these lesions with identical prompts predicting diagnostic probabilities, triage (urgent vs routine), and rationale. Outcomes included sensitivity, specificity, AUROC, F1, and subgroup equity. Model rationales were reviewed for interpretability, and subset re-prompting tested reproducibility for translational robustness. Results/Anticipated Results: Across six models, sensitivity range was 0.89–1.00, specificity 0.21–0.65, AUROC 0.77–0.87, and F1 scores 0.72–0.81. GPT-5 achieved the most balanced performance (0.92 sensitivity, 0.65 specificity, AUROC 0.87, F1 0.81), while Gemini 2.5 Pro and Flash reached perfect sensitivity but low specificity (0.21–0.25). Claude Sonnet-4 showed near-perfect sensitivity (0.99) but over-called benign cases (0.24 specificity), while Opus-4 had the lowest sensitivity (0.89). Urgent triage aligned with dermatologist biopsy patterns (87–97%), and sensitivity was consistent across sex and skin type (p ≥ 0.29). Subset re-prompting produced similar results, supporting reproducibility. Model rationales reflected dermatologic reasoning, supporting interpretability, and translational readiness. Discussion/Significance of Impact: Multimodal AI models showed balanced diagnostic performance for dermatology triage, with platform-specific trade-offs between sensitivity and specificity. Subgroup equity, interpretable rationales, and subset reproducibility define key elements for reliable translation into dermatology workflows and prospective validation.

Objectives/Goals: This project applies a novel approach (goal-activity congruence) to evaluate a project-based CHW certification course in Houston, Texas. Objectives: (1) improve understanding of learner motivation and (2) develop alternative assessment methods for non-degree healthcare training programs. Methods/Study Population: Data were collected using voluntary pre-post-training surveys including self-reported measures of expected and experienced growth toward learner-articulated goals. As part of the post-training survey, learners were shown text from individual goals developed at the beginning of the course and asked to connect these goals with instructor defined activities from the training. Learners also responded to multiple open-ended items focused on the contribution their training experience made to their career journey and their biggest lessons learned. Data were analyzed using descriptive statistics (goal-activity congruence and self-reported growth) and thematic analysis of qualitative responses. Results/Anticipated Results: Response rates were 50% at entry and 43% at exit. Most respondents reported experiencing “lots” of progress toward their goals (65%), and 93% reported that the training was largely or partly responsible for this progress. Learners reported that the most helpful program activities contributing to their goals included: the community health project (69%), motivational interviewing role plays (66%), and the Logic model assignment (66%). Qualitative themes that emerged included: development of knowledge and motivation to help their community, learning to develop skills and gain access to resources that will contribute to career and community, and helped them to better understand how to help others. Discussion/Significance of Impact: This study demonstrates the viability and value of including activity-goal congruence as a part of training program evaluations. While providers should not be solely guided by learner goals when developing training curriculum, considering them will lead to more effective and well-received trainings.

Objectives/Goals: To implement and evaluate a Smartsheet-based system that centralizes management, tracking, and credentialing for the NJ ACTS Clinical Research Coordinator digital badging program, improving efficiency, data integration, and measurable workforce development outcomes. Methods/Study Population: The NJ ACTS CRC digital badging program was integrated into a Smartsheet platform designed to unify data across JotForm, Qualtrics, REDCap, Canvas LMS, and Accredible. Automated workflows track learner enrollment, module completion, and credential issuance in real time. Participants include CRCs and trainees across academic and clinical settings. The platform’s dashboards and automated reports support continuous monitoring, feedback collection, and competency validation. Data from initial cohorts were analyzed to assess usability, process efficiency, and accuracy of training metrics across systems. Results/Anticipated Results: Integration of Smartsheet has improved onboarding efficiency, reduced administrative burden, and enhanced visibility into learner progress. Automated credentialing through Accredible provides timely recognition of competencies. Early results demonstrate increased completion rates and more consistent tracking across partner sites. The unified system enables data-driven decision-making and facilitates the scalable expansion of CRC training efforts within and beyond NJ ACTS institutions. Discussion/Significance of Impact: Smartsheet integration enhances the infrastructure for digital badging and workforce tracking, providing a replicable and scalable model to standardize CRC training nationally and advance competency-based education in translational science.

Objectives/Goals: To culturally adapt and validate the Spanish version of the UCLA Loneliness Scale-10 for the Puerto Rican population and to determine the prevalence and characteristics of loneliness among individuals aged 60 and older across various regions of the island. Methods/Study Population: A quantitative, descriptive, cross-sectional study was conducted including cultural adaptation and psychometric validation of the Spanish UCLA Loneliness Scale-10. A pilot with 47 older adults from northeastern Puerto Rico preceded a stratified random sample of 400 adults aged 60+ from public housing in 24 municipalities, covering Puerto Rico’s eight regions. Sample size was calculated with 99% confidence and 5% error margin. Recruitment occurred Dec 2024–Mar 2025. Inclusion: age ≥60, Spanish-speaking, residing in Puerto Rico. Cognitive function was screened using MMSE. Results/Anticipated Results: Most participants were female (78.3%) and aged 60-70 (59.5%). Over half lived alone (54.3%), and 82% earned under $10,000 annually. The UCLA Loneliness Scale showed high validity (CVI=0.99) and reliability (α=0.88). Loneliness prevalence was 39.8%, mostly moderate, with 4.25% severe. No significant differences in loneliness by gender, marital status, or family composition were found. However, low income, limited family accessibility, poor neighborhood relations, and mobility issues were significantly linked to higher loneliness. Social activity showed a trend toward reducing loneliness but was not statistically significant. Discussion/Significance of Impact: This study with 400 Puerto Rican older adults confirms the culturally adapted UCLA-10 scale’s reliability (α=0.88), crucial for accurately measuring loneliness in this population. Findings reveal 39.8% loneliness prevalence, influenced by socioeconomic and social factors, underscoring the need for culturally sensitive interventions.

Objectives/Goals: Increase enrollment of populations reluctant to participate in precision health and Alzheimer’s disease research by leveraging trusted partnerships, responsive engagement, and a registry-enabled referral pathway. Methods/Study Population: Using a four-way partnership (Institute of Clinical and Translational Sciences Precision Health, research lab partners, Balls-Berry Lab, and community organizations), we implemented a community tailored engagements for adults aged ≥65 at risk for Alzheimer’s disease. Activities included Alzheimer’s education sessions, a sleep-health dinner forum, and direct referrals to active studies. Participants were identified via the local research registry and community networks. Trusted messengers led discussions, facilitated warm hand-offs to coordinators, and supported structured follow-up to sustain engagement and retention. Results/Anticipated Results: In 2025, community events reached >170 participants; >95% identified as Black/African American, and >65% were aged ≥65 years. Across events, about a fourth completed research inquiry cards, with on-site warm hand-offs increasing direct enrollment in active studies. Engagements strengthened trust, improved research literacy, and established a replicable, scalable model. Anticipated 2026 outcomes include expansion to additional precision-health domains, enhanced longitudinal tracking of referrals and enrollments, and broader implementation with urban and suburban partners. Discussion/Significance of Impact: Culturally grounded, community engaged strategies coupled with registry-enabled referrals can measurably improve recruitment, retention, and trust in precision health research, addressing persistent disparities in Alzheimer’s disease studies and accelerating equitable translation.

To contribute to the ongoing discussion on the role of pitch processing in grammar learning, this study examines the extent to which pitch statistical learning (pitch statistical learning (SL); the ability to detect and internalize pitch patterns in auditory input) affects second language (L2) morphosyntax learning outcomes. In the context of 93 Japanese learners of English, piece-wise regression analyses were conducted to compare the roles of their pitch SL abilities and pitch acuity in L2 morphosyntactic knowledge. The results revealed a weak but significant positive correlation between pitch SL and morphosyntactic knowledge, whereas pitch acuity showed no significant association. Further analysis identified a threshold effect: pitch SL has a strong association with morphosyntactic knowledge for learners with lower pitch SL abilities, but not for those with higher pitch SL abilities. These findings suggest that the lack of pitch SL ability could substantially slow down L2 morphosyntactic learning.

Objectives/Goals: 1.To develop the next generation of translational scientists in PR. 2. To equip pre-university/undergraduate students with the necessary skills, knowledge, and experiences for their academic and professional development from a holistic perspective of life. 3. To strengthen the technological-translational science (TS) infrastructure. Methods/Study Population: Develop the Center for Research Education and Science Communication-Counseling Opportunities (CRESCO) to provide support to PuS and UgS in TS skills, statistics, scientific writing, emerging technologies, mentoring-tutoring and counseling-orientation; organize/launched the ACADEMIA-TS (ACAD-TS) with the inaugural activity to provide training/student development in TS to PuS and UgS, including peer-mentoring with graduate students (GS); create the Small Project in Translational Science (SPTS) program to offer PuS and UgS hands-on experiences with participation in up-to-date research in TS under the mentorship of a principal investigator-mentor; offer the Title V Annual Symposium in TS; and acquire computers/laboratory supplies/equipment to health sciences undergraduate schools. Results/Anticipated Results: CRESCO established a training infrastructure by acquiring 535 licenses (Consensus, Scite.ai, Mind-Graph) to integrate AI into research and offered 122 mentoring sessions. There were 296 participants in four new workshops. In ACAD-TS’ inaugural activity (~200 attendees), 67 PuS expressed interest in the ACAD-TS; 12 PuS are part of it, and 38 PuS participated in a counseling workshop. The SPTS program integrated course enrolled 10 students (8 from other UPR campuses) and created five teams involving 26 students (8 PuS, 16 UgS, 2 GS) mentored by 5 Principal Investigators (PIs), representing 15 institutions. The 14th Annual Symposium had 136 attendees, with a 100% satisfaction rate (n=44). The technology/TS infrastructure was upgraded with 50 new computers and supplies/minor equipment for health science schools. Discussion/Significance of Impact: Established a comprehensive model to develop early-career translational scientists, including a course, SPTS, and counseling workshops. Integrating AI tools, focused mentorship, and enhanced infrastructure strengthened participants’ integral development, confirming this model boosts research capacity for the future TS workforce.

Objectives/Goals: The plasma membrane (PM) is the nexus for cell signaling, where lipid composition governs receptor organization and T cell function. We aim to define PM dynamics in T cell states and develop PM-based strategies to preserve anti-tumor activity. Methods/Study Population: As such, we induced a dysfunctional T cell state, known as T cell exhaustion, through chronic stimulation or TGF-β1, hypoxia, and tumor cell co-culture and measured membrane biophysical properties through ratiometric confocal imaging of molecular probe Di-4-ANEPPDHQ. Complementary biochemical data from shotgun lipidomic analysis, immunofluorescence staining, and biochemical fluorescent assays paint a more complex picture of membrane fluidity changes during T cell exhaustion. Results/Anticipated Results: In both cases, we observed decreased PM rigidity compared to acute or normoxic T cell activation, specifically in T cells with upregulated PD1, LAG-3, and Tim-3. Dysfunctional T cells also exhibit changes in specific lipid species. This includes increased free cholesterol and decreased esterified cholesterol among other species. Discussion/Significance of Impact: Adoptive cell therapy is limited in solid tumors due to a hypoxic, suppressive TME that drives T cell exhaustion. Our data suggest exhausted T cells have fluid plasma membranes that impair synapse formation. Future work will validate this in patient-derived xenograft/TCR-T models that will pave the way for clinical translation.

Objectives/Goals: To assess the association between pollution and CVD outcomes in a high-risk CAD population, and investigate how social drivers intersect with this association. Methods/Study Population: 1,602 participants enrolled in the Emory Cardiovascular Biobank were stratified into high vs. low pollutant exposure groups based on PM₂.₅ (median 10.6 μg/m³), NOx (median 39.4 ppb), and CO (median 635 ppb) levels. Demographics, cardiovascular (CV) risk factors, comorbidities, and SVI domains including socioeconomic status (RPL_THEME1), household characteristics (RPL_THEME2), racial/ethnic minority status (RPL_THEME3), housing and transportation (RPL_THEME4), and overall SVI ranking (RPL_THEMES) were compared between groups. Cox proportional hazards models were used to assess associations between pollutants and CVD outcomes (CV death, myocardial infarction [MI], stroke, heart failure, and the composite MACE. Results/Anticipated Results: Higher PM₂.₅ exposure was associated with a greater prevalence of hypertension (82.7% vs. 74.6%, p<0.001), female sex (39.7% vs. 34.1%, p=0.023), and elevated SVI scores (RPL_THEME1–4, all p<0.05). Similar gradients were observed across NOx and CO strata, particularly in SVI metrics (p<0.001). In fully adjusted models, MACE were associated with PM₂.₅ (HR 1.73, 95% CI: 1.22–2.44, p = 0.002) and CO (HR 1.00, 95% CI: 1.0005–1.003, p = 0.005) levels. Additionally, HF admissions were associated with PM₂.₅ levels (HR 1.16, 95% CI: 1.05–1.28, p = 0.003). SVI measures interacted significantly with the impact of NOx on HF risk [RPL_THEME1 (HR 1.03, p = 0.033) and RPL_THEME2 (HR 1.05, p = 0.008)] and stroke risk [RPL_THEME4 (HR 1.07, p = 0.025)]. Discussion/Significance of Impact: In patients with CAD, higher PM₂.₅ exposure is independently associated with risk of MACE. Social vulnerability amplified the adverse risk relationships for NOx exposure highlighting the need to consider neighborhood-level risk in pollution-related CV disease prevention.

Objectives/Goals: Integrating lived experiences of people like patients and caregivers across translational research increases responsivity to local need and likelihood of meaningful results. The Community Health Consultant (CHC) Program is a dynamic, formalized source of lived experience advisors for the Institute of Clinical and Translational Sciences (ICTS). Methods/Study Population: Established in 2023, the CHC Program comprises: 1) ongoing recruitment of individuals committed to sharing their lived experiences and perspectives with researchers; 2) creation of profiles which detail an individual’s neighborhood involvement, lived experiences with health and social conditions, and interest in types of advisor activities; 3) matchmaking individuals with relevant lived experiences to community studios, boards, and community grant review processes; 4) a formalized compensation structure which prioritizes efficiently compensating consultants at a rate that demonstrates the value that lived experiences brings to research processes; and 5) consistent feedback loops with the CHC Program as a whole as well as with individual consultants. Results/Anticipated Results: To date, 152 individuals with wide-ranging backgrounds have joined as lived experience advisors to ICTS research. A sample of their collective individualities: * Chris is a community health worker in East Saint Louis. He wanted to be a liaison to the areas he says researchers do not go. “Researchers need to listen to people like me,” he says, “the urban community feels like it’s lost its voice.” * Terry is a mayor in north St. Louis. He says if a researcher is focused on a particular group, they should get “real feedback on how we feel these things benefit us or not benefit us.” * Melvia is an active senior citizen. She says, “The connection to the community is a wealth of information.” In 12 months, activities have included community studios (46), grant review (32), advisory committee linkages (6), and faculty lunch meetings (3). Discussion/Significance of Impact: A dynamic, formalized source of lived experience advisors is critical for mobilizing engagement activities to support ICTS researchers. A community engagement program acts as a natural coordinating hub, building and maintaining individual relationships while matchmaking and providing warm handoffs for lived experience linkages.

Objectives/Goals: Translational research teams span varied roles, disciplines, and institutions. They rely on information to collaborate, communicate, and coordinate. Information should flow seamlessly for collaborative success, yet we know little about the collective information needs and challenges of such teams, representing a translational science problem. Methods/Study Population: We report on the Information Management Prototype for Clinical and Translational Research (IMPACT-CTR) study which explored how clinical and translational research teams (CTRTs) manage their information while conducting collaborative research. Participants across 11 US-based CTRTs (n=52) participated in brief surveys and interviews about their collaborative processes. We are following the Translational Team Science Hierarchy of Needs (Kelly et al., 2023) framework in our thematic analyses, where we are sequentially examining: (1) the foundation of information infrastructure (tools and resources), (2) teams’ information management practices, and (3) how these practices affect psychological safety of team members, which then impact “translational nirvana” or the research synergy of CTRTs. Results/Anticipated Results: Preliminary analysis revealed that information was crucial to CTRTs’ functionality but often overlooked. Team members moved through the research lifecycle by juggling numerous types of information spread across multiple tools, while balancing their personal information styles with those of the collective. Subsequent analyses will investigate the challenges, workarounds, and lessons CTRT members have learned while managing their information and relying on each other as information resources, and the extent to which these factors impact their scientific and operational work, as well as their team culture. We will thus develop and present a conceptual framework of how CTRTs’ information behaviors can facilitate or impede high-impact collaborative research. Discussion/Significance of Impact: We will present reproducible team science practices that can enhance the process of scientific research through evidence-based information management practices that are both effective and feasible for CTRTs. In doing so, we will identify information-related barriers that hinder the efficiency of the translational research continuum.

Objectives/Goals: To evaluate how establishing a food pantry through partnerships with Bread of the Mighty and Feeding Northeast Florida influenced community engagement at UF HealthStreet between 2023 and 2025. Methods/Study Population: UF HealthStreet, a community engagement program, became part of the Healthy Pantry network through partnerships with Bread of the Mighty and Feeding Northeast Florida. 14,678 people are part of the UF HealthStreet registry and 47% self-reported experiencing food insecurity. To evaluate impact, engagement data from two 12-month periods were compared: June 1, 2023–May 31, 2024 (pre-food pantry) and June 1, 2024–May 31, 2025 (food pantry year). Metrics included HNAs, referrals, and visits analyzed to assess engagement changes. Results/Anticipated Results: Community engagement increased from 2,705 visits (pre-pantry) to 7,726 (post-pantry), including 4,243 connected through pantry visits. The number of people visiting UF HealthStreet rose from 1,210 (pre-pantry) to 2,286 (post-pantry), demonstrating broader community reach. Average monthly HNAs rose from 35 to 52 (~1.5x increase). Referrals grew slightly from 2,093 to 2,129, reflecting sustained service linkages amid expanded participation. Becoming a Healthy Pantry site strengthened UF HealthStreet’s capacity to address food insecurity and reduce health disparities. Discussion/Significance of Impact: Food bank partnerships expanded UF HealthStreet’s reach and strengthened community trust. More visits and return participants reflect deeper engagement. Integrating food access into health outreach advances translational science and helps address health disparities.

Objectives/Goals: Meaningful community engagement is critical to trustworthy translational research, yet engagement strategies outside structured meetings are rarely described. For a study of HIV PrEP implementation on college campuses, a Community Involved Board (CIB) participated in between-session activities (BSAs), described below. Methods/Study Population: Six CIB members were recruited to attend bi-monthly sessions from 2024 to 2025. The research team developed each BSA from relevant components of key theoretical frameworks including Labor Process Theory, Critical Pedagogy, and Community-Based Participatory Research. These frameworks informed the design of activities such as critical reflection journals, media audits of health messaging on public and social platforms, and synchronous activities such as CIB-led campus tours for researchers. BSA “responses” informed the direction of subsequent sessions. The five BSAs were optional, and participants were compensated $15–$25 per activity. Feedback from research team debriefing sessions and CIB member evaluations guided BSA refinement and implementation. Results/Anticipated Results: CIB members completed nearly all BSAs and perceived their input as meaningfully shaping session and project goals. Evaluations and debriefing notes revealed that BSAs promoted continuity in participation, individual and group agency, and reflexivity among CIB members. Researchers noted improved depth, specificity, and sharing during CIB sessions and increased communication between CIB members and the research team regarding logistics, successes, and challenges related to BSA completion. Reported barriers to BSA implementation included competing demands (from family, work, and school) and inconsistent expectations for BSA completion. The research team addressed challenges by offering timeline flexibility, altering compensation structures and reflexively examining and discussing power disparities. Discussion/Significance of Impact: Translational research relies on responsive and sustainable community engagement. The BSA approach demonstrates how intentional, theory-informed activities can translate engagement principles into practice, maintaining meaningful and authentic collaboration beyond structured community meetings.

Objectives/Goals: The goal of this study was to determine if there are the peripheral immune system changes in persons undergoing treatment with lecanemab, and whether those changes are associated with the incidence of amyloid-related imaging abnormalities (ARIA), in order to identify strategies for improving the safety profile of anti-amyloid antibodies. Methods/Study Population: Three pairs of age, sex, APOE genotype, and infusion-matched individuals were selected from a study population at Norton Neuroscience Institute Memory Center (NNI-MC), based on the development of ARIA. Peripheral blood mononuclear cells isolated from these case–control subjects were collected and cryopreserved. Thawed cells were run through a deep sequencing pipeline, including single-cell RNAseq, CITEseq TCR clonality (V(D)Jseq), metabolomics, and lipidomics. Multi-omic data was integrated and analyzed using R (scRNAseq, CITEseq, and V(D)Jseq) and MetaboAnalyst (Metabolomics and Lipidomics). Deidentified clinical data was obtained to correlate to sequencing findings, including cognitive exam scores, MRI scans, and relevant lab values. Results/Anticipated Results: We noted an increase in lymphocytes in ARIA-positive subjects, with expansion in CD8+ T-cells – particularly CD45-RA expressing T-effector memory (TEMRA) subsets. These TEMRA cells expressed large clonal expansions in cells programmed for antigen response, cytotoxicity, and metabolic shifts. We found that in ARIA+ subjects, there was a pro-inflammatory glycolytic shift, accompanied by CD8-driven lipidomic changes. To determine potential effects of TEMRAs on the CNS, we mapped our data onto previously published ARIA+ patient brain transcriptomes (van Olst et al., 2025). TEMRA CD8s from our dataset showed increases in in silico communication with the vascular endothelium, indicating priming of these cells for cerebrovascular engagement. Discussion/Significance of Impact: Together, this first-of-its-kind data in human subjects receiving lecanemab infusions may point to peripheral immunity as a driving factor – and potential biomarker and therapeutic target for – ARIA pathogenesis, allowing for increased safety of these drugs in the highest risk AD populations.

Objectives/Goals: To benchmark the extent to which variability in automated WMH quantification influences stroke and dementia risk stratification by characterizing differences in volume estimates and spatial concordance across three segmentation tools (BIANCA, SAMSEG, and nnU-Net). Methods/Study Population: This retrospective, cross-sectional study will analyze de-identified clinical brain MRI scans from patients aged ≥50 years, including those with and without prior stroke, obtained from institutional imaging repositories. Eligible scans include co-registered T1-weighted and FLAIR sequences. Scans with poor image quality and scans from patients with multiple sclerosis, other demyelinating disorders, or brain tumors will be excluded. WMHs will be segmented using three tools: BIANCA (supervised k-NN classifier), SAMSEG (unsupervised Bayesian model), and nnU-Net (self-configuring deep learning). Agreement in WMH burden will be assessed with intraclass correlation coefficients (ICC[3,1]) and spatial concordance with Dice similarity coefficients (DSC). Bland-Altman analyses will evaluate bias. Results/Anticipated Results: We will analyze 600 brain MRI scans. All three tools are expected to detect similar WMH spatial distributions, though total WMH volume estimates may differ. nnU-Net may yield higher WMH burden estimates than BIANCA or SAMSEG. WMH burden will be neuroradiologist-adjudicated to establish the gold standard, against which concordance for each tool and inter-tool agreement will be assessed using ICC[3,1] and DSC. We anticipate moderate-to-high agreement, but tool-specific variability could influence reproducibility and interpretation of WMH burden for future WMH-related research studies. This study will quantify the extent of variability among tools in clinical brain MRI scans and evaluate whether these differences could meaningfully alter future stroke risk classification thresholds. Discussion/Significance of Impact: This study will benchmark automated segmentation tools for WMH-related research by standardizing WMH quantification to improve reproducibility and reliability for stroke and dementia risk stratification. Establishing tool-specific benchmarks may also guide integration of automated WMH measures into clinical decision-support systems.