Objectives/Goals: This study aims to identify socioeconomic, clinical, and behavioral risk factors of non-adherence for adults with hypertension and evaluate implications for future treatment strategies. Methods/Study Population: We will conduct a systematic review following PRISMA guidelines. Eligible studies are peer-reviewed RCTs and observational designs assessing factors associated with antihypertensive medication adherence among adults (≥18 years) with hypertension living in North America or Europe. Studies must report adherence as the primary outcome. Studies will be excluded if they are not peer-reviewed, original research articles, published in a non-English language, reviews or meta-analyses, or studies of an intervention aimed at improving adherence. Abstract and title screening, full paper review, and data extraction will be performed in Covidence by two reviewers with conflicts resolved by consensus. Results/Anticipated Results: A total of 5660 records were imported for screening after duplicate removal. Following title and abstract screening, 4990 studies were excluded as irrelevant, leaving 670 records for full-text review. Of 611 full texts reviewed, 491 studies were excluded and 39 are pending conflict resolution. Currently, 119 studies are marked for data extraction. Data to be extracted will include socioeconomic, demographic, clinical, and behavioral determinants of antihypertensive medication adherence. Quality assurance will involve dual independent extraction. Preliminary trends suggest wide variability in study designs and adherence definitions across North American and European populations. Discussion/Significance of Impact: Findings will clarify key predictors of antihypertensive medication non-adherence and highlight gaps in evidence. Results will guide future adherence-improving strategies and inform design of simplified regimens, digital tools, and population-specific hypertension management policies.

Objectives/Goals: The CTSA at the University of Michigan, MICHR, has conducted a sequential mixed-methods needs assessment of a network of over 250 dissemination and implementation scientists working at the university. The purpose of this evaluation is to identify the research training needs of this network and to inform efforts to improve the networks’ productivity. Methods/Study Population: An IRB-approved sequential mixed-methods needs assessment of a network of over 250 dissemination and implementation scientists was conducted. First, surveys were sent to all members of the network using Qualtrics. This survey was designed to measure the challenges and facilitators encountered by members of this network, using response categories aligned with the Translational Science Benefits Model (Luke et al., 2018) to facilitate the identification of programmatic improvement goals. The survey also asked questions regarding network members’ training preferences, and their current plans to design specific types of implementation science clinical trials (Fortney et al., 2024). Survey respondents also indicated their availability for subsequent interviews to explore their career and training paths. Results/Anticipated Results: Surveys were sent out to over 250 individual members of the Implementation Science Network supported by MICHR. This network includes 249 U-M employees representing 44 departments or units, 7 individuals from Veterans Affairs and 16 from other Institutions, and of these 32 individuals (11%). Despite this low response rate, the results clearly indicated that accessing D&I training/educational resources, or learning about relevant measures, metrics and testable strategies was a major barrier to 71% of network members, with 61% particularly interested in training on developing and testing strategies. Most respondents (54%) reported that having more financial resources was a facilitator of their work and 62% volunteered to be interviewed about their careers. Interviews are being conducted and analyzed. Discussion/Significance of Impact: The results of this evaluation suggest dissemination and implementation scientists need more formal training programs, specifically ones focused on the selection of implementation strategies for testing in pragmatic and hybrid clinical trials. This work provides a rigorous and reproduceable methods for CTSAs to conduct needs assessments.

Objectives/Goals: Alterations in the patterns of cerebrospinal fluid (CSF) have been proposed to play a role in the development of symptoms related to Chiari I malformation (CMI). We aim to use 4D MRI to evaluate CSF fluid dynamics in CMI, including CSF pressures and local flow vectors, and their association with pre- and post-operative symptoms. Methods/Study Population: Study Population: Pediatric and adult patients diagnosed with Chiari I malformation (caudal descent of cerebellar tonsils ≥ 5 mm below the foramen magnum) at Washington University in St. Louis. Methods: Patients underwent CSF 4D flow MRI studies on 3.0T MRI at Washington University in St. Louis. The acquired imaging data will be preprocessed to unwrap velocity aliasing, denoise, and account for MRI-associated eddy artifact. Flow visualization and quantification will be performed in order to calculate patient-specific flow patterns, such as flow vortices and bidirectional flow, and vectors, such as peak velocity, at CSF spaces of the brain and spine. Clinical data, including demographics, symptom history (e.g., headache), physical exam findings, and presence of syrinx have already been collected. Results/Anticipated Results: We anticipate that patients with greater preoperative CSF flow heterogeneities and abnormalities of flow vectors will be associated with a higher likelihood of symptoms, and that patients with greater postoperative normalization of these variables will be more likely to experience symptom relief. Discussion/Significance of Impact: The role of CSF hydrodynamics in CMI remains incompletely understood. We aim to examine whether alterations in CSF flow may explain why some patients are asymptomatic, while others suffer debilitating headaches and cranial nerve palsies. The results would expand scientific knowledge and may aid in identifying patients likely to benefit from surgery.

Objectives/Goals: Heart rate variability (HRV) is the variation in time between each heartbeat and an important biomarker of autonomic nervous system function, with higher HRV generally associated with improved parasympathetic tone and cardiac health. The most reliable measurement is during sleep, but sleep and HRV are both understudied in cirrhosis and HE. Methods/Study Population: We longitudinally assessed sleep and resting cardiovascular biomarkers in a cohort (n=119) of patients with cirrhosis using Oura, a commercially available fitness tracker. Baseline clinical data, psychometric hepatic encephalopathy score (PHES) and 6 months of passive sleep data collection were obtained. 117 participants enrolled, 6 collected no sleep data, 13 did not complete PHES; 10,065 nights (n=98) were available, and 9,692 were analyzed after outlier trimming (top and bottom 1% of data). Mixed effects modeling (MEM) assessed associations. Pre-specified covariates included age, gender, sodium, albumin, bilirubin, INR, and ascites. Missing data was not imputed. Results/Anticipated Results: In univariable analysis, impaired cognition by PHES was associated with increased average HRV (B 5.2 95%CI 0.25, 10.1 p=0.04) but not respiratory rate, heart rate, or lowest measured heart rate. CTP Score (B -1.8 95%CI -3.0, -0.6 p<0.01) and INR (B -6.1 95%CI -11.6, -0.5 p=0.03) were inversely associated with HRV. Higher baseline albumin (B 3.9 95%CI 0.34, 7.4 p=0.03) and sodium (B 1.0 95%CI 0.18, 1.75 p=0.02) were associated with increased HRV, while age, gender, and creatinine did not significantly associate with HRV. In a MEM adjusting for the pre-specified covariates, the association was greater (B 8.85 95%CI 3.85, 13.9 p<0.01), remaining significant after log-normalizing HRV. In a sensitivity analysis adjusting for current alcohol use or prior variceal bleed, the results were unchanged. Discussion/Significance of Impact: In a large cohort in cirrhosis, cognitive impairment was associated with increased HRV, in contrast to other markers of liver disease, where HRV was reduced and unrelated to other cardiovascular measures. This paradoxical relationship, if validated, could be developed as a longitudinal digital biomarker for the detection of cognitive impairment in HE.

Intravenous (IV) low-dose ketamine has emerged as a promising treatment for patients with treatment-resistant depression (TRD). However, its impact on cognitive functioning remains unclear. This systematic review examines the cognitive and executive effects of IV ketamine in TRD, focusing on their relationship to depressive and suicidal outcomes. A systematic search of Cochrane, MEDLINE, Embase, and PsycINFO databases was conducted up to May 15, 2025, using the terms depression, cognition, and ketamine. This review was conducted in accordance with the PRISMA guidelines, and the protocol was registered in PROSPERO (ID: 1160487). Risk of bias was evaluated using the Cochrane RoB 2 tool for randomized trials and the ROBINS-I tool for non-randomized studies. Twenty-one studies, comprising approximately 900–1,180 participants with TRD, assessed cognitive domains of processing speed, working memory, attention, verbal and visual memory, cognitive flexibility, and executive control. Procognitive effects were frequently observed in processing speed and working memory, while attention results were preserved or modestly improved, and verbal and visual memory results were heterogeneous. Executive control, particularly inhibitory performance on Stroop paradigms, improved in several trials. Two studies directly examined cognition as it relates to suicidal behaviors. No cognitive deterioration was reported. Subanesthetic IV ketamine appears to preserve and enhance specific cognitive functions in TRD, notably across processing speed, working memory, and executive control. These procognitive effects, particularly in executive control, may mediate ketamine’s antisuicidal action. Standardized longitudinal studies are warranted to clarify their durability and clinical significance.

Objectives/Goals: The Human Immune Dysregulation Evaluation Framework (Hi-DEF) quantifies myeloid dysregulation in infectious and non-infectious illness using peripheral blood gene expression (Moore, Nat Med). We evaluated immune dysregulation in obesity and quantified the changes in dysregulation due to lifestyle and medical interventions. Methods/Study Population: We assessed the association of obesity with myeloid dysregulation in the Framingham Cohort using linear regression. In two additional datasets (GSE66175, GSE19790), we assessed the effect of dietary interventions and bariatric surgery on myeloid dysregulation using paired Wilcoxon rank sum test pre- and post- intervention and Pearson’s correlation. Results/Anticipated Results: In the Framingham cohort (n=5321), myeloid dysregulation score was associated with BMI (p=2.2e-6) after correcting for age and sex. Patients assigned to diet/exercise experienced significant reductions in myeloid score after 3 months (n=63, p=1.2e-7), which was not seen in controls (n=63, p=0.29). Change in myeloid score was significantly correlated with change in weight loss (r=0.32, p=0.006). This reduction in myeloid dysregulation was also seen post-bariatric surgery (n=11, p=0.0001). Discussion/Significance of Impact: Patients with obesity have significantly higher myeloid dysregulation compared to healthy subjects, which is modifiable with lifestyle and medical interventions. These results suggest that we may be able to quantify and monitor immune dysregulation from obesity which may place these patients at risk for worse outcomes.

Objectives/Goals: This proposed study aims to explore whether geographic patterns exist in the prevalence of anxiety diagnoses among adult patients (ages 18–64 years) using EHR data from three counties in North Carolina. Methods/Study Population: This proposed study will employ a retrospective, cross-sectional analysis of de-identified EHR data, examining anxiety diagnoses across geographic locations. To analyze the data, a multi-step approach will be used, combining geospatial analysis, descriptive statistics, and inferential statistical tests. Results/Anticipated Results: Findings may reveal geographic disparities in anxiety prevalence, highlighting potential social determinants of mental health and social risk factors. Identifying spatial patterns could inform targeted interventions to improve mental health equity and resource allocation in high-burden areas. Discussion/Significance of Impact: Understanding the geographic distribution of anxiety diagnoses can help guide policy and healthcare efforts to address mental health disparities. This study contributes to the growing body of research leveraging EHR data to examine population-level mental health trends.

Objectives/Goals: Our UAB OBGYN team is collaborating with the West Alabama (AL) Maternity Care Coalition (WAMCC) and using implementation mapping and mixed methods to co-develop and test a digital implementation strategy at the individual and community level. The goal is to mitigate mistrust and improve the accessibility of maternity care in rural areas. Methods/Study Population: UAB OBGYN and the WAMCC will partner with Ashmi Health and the West Alabama Area Health Education to co-develop and test the implementation strategy, MOM (Mothering Our Mothers) Connect (MOM-C). The MOM-C is an adaptive progressive web application that includes contextually tailored health information, local resources, and local community health worker (CHW) support. This three-phase research includes 1) co-developing and finalizing the implementation strategy using focus groups and implementation mapping; 2) pretesting and finalizing the strategy components with people of reproductive age (n = 20) and local CHWs (n = 2–3); and 3) finalizing the strategy and implementation map. Results/Anticipated Results: Data collection led to the refinement of MOM-C and the development of a CHW training course. Our team also developed additional, complementary implementation strategies that included effective dissemination methods. Plans and metrics for case tracking, resource sharing, usage analytics, and user behavior data will be developed to measure the association between the implementation strategies and both primary and secondary outcomes. Primary outcomes include utilization of perinatal healthcare and social/community resources and self-efficacy. Secondary outcomes include provider and medication adherence, complications, depressive/anxiety symptoms, perceived stress, and quality of life. Discussion/Significance of Impact: Digital health interventions are an essential and cost-effective public health tool for the efficient delivery of health education and healthcare services, especially in care deserts. In low resource and low trust contexts, digital health interventions are strengthened when they are combined with CHW services and adapted for the local context.

Objectives/Goals: Effective collaboration is needed to respond to the scientific challenges of our times. A related challenge is how to support individual and team learning for such collaborations. Our project goal is to describe and evaluate team training approaches and lessons learned at one CTSA since the inception of#_msocom_1 its Team Science Core in 2017. Methods/Study Population: The Institute of Translational Science (ITHS) Team Science Core has offered team science-focused training and education for nearly eight years. During this time, our approach has evolved to meet changing needs and contexts. Initially, most of our offerings were in person, including an annual multi-day in-person workshop for interdisciplinary research teams (3 or more individuals from 2 or more disciplines). During and since the COVID-19 pandemic, the majority of our offerings have shifted to online trainings which has helped expand regional access. Throughout this period, qualitative and quantitative data have been collected about and from participants. We have carried out mixed methods analyses to describe and evaluate these team training approaches and lessons learned. Results/Anticipated Results: Since 2017, the ITHS Team Science Core has offered ~250 trainings for more than 6000 individual participants (and >500 interdisciplinary research teams). Participants included students (undergraduate and graduate), trainees, faculty, clinicians, and research professionals from the WWAMI (Washington, Wyoming, Alaska, Montana, Idaho) Region and beyond. Feedback from participants in workshops, seminars, classes, and other activities has been overwhelmingly positive; 80–95% of respondents agreed or strongly agreed with the statement that “participation will improve my team’s collaboration.” Qualitative responses (short answers and interviews) illustrate ways that individuals and teams applied their learning to improve communication, clarify roles, and increase confidence in using team tools. Discussion/Significance of Impact: Clear benefits of participating in team science education and training were reported. A shift to virtual formats increased accessibility and regional representation. Qualitative interviews and short answer responses offered an enriched understanding of how team training influenced collaboration and implementation of team science practices.

Objectives/Goals: Analyze risk factors among college students and their likelihood of experiencing or perpetrating sexual violence. Critique the process to develop a screening tool to match students to existing programming. Examine principles of implementation science in overcoming barriers to connect each student to the most appropriate prevention programming. Methods/Study Population: Research questions: What needs to be in a screening tool to gauge each incoming college student’s risk factors and likelihood for future sexual violence victimization and perpetration? How can the tool be designed using principles of implementation science with end-user feasibility in mind? For this protocol, I will initiate a participatory research process to guide the development of a screening tool for incoming college students in a mid-western sample of the USA to assess risk factors for sexual violence victimization and perpetration. I will assemble a Technical Expert Panel to develop the screening tool using existing standardized measures. I aim to recruit a diverse panel of researchers and practitioners in sexual violence prevention, including sexual assault survivors and peer educators. Results/Anticipated Results: The anticipated result will be a screening tool to predict the likelihood of victimization and perpetration for each incoming college student over one academic year. Next steps would be to pilot-test the screening tool to determine its effectiveness. The long-term goal would be to match each student to the most appropriate evidence-based prevention program based on individualized screening results. This could include existing evidence-based programs that prevent or decrease severity of victimization, revictimization, alcohol-facilitated victimization, perpetration, perpetration among high-risk students, and perpetration among fraternity members. Considering barriers and stakeholder engagement from the onset of the project aims to increase the feasibility of implementation in practice. Discussion/Significance of Impact: Quantifying an approximation of how many students would benefit from which types of programming can help colleges determine where to invest their time and resources to best prevent sexual violence. Guiding each incoming student to the most appropriate evidence-based prevention program could decrease rates of campus sexual violence.

Objectives/Goals: The purpose of this study was to examine associations between prenatal family and community exposures and early childhood DNA methylation (DNAm) at genomic regions related to energy regulation or fat deposition. Results could contribute to the understanding of disparities in metabolic health risk among children from disadvantaged communities. Methods/Study Population: This is part of a cross-sectional study of mother–child dyads recruited from a previous RCT with pregnant women in California who had a pre-pregnancy BMI of 25–40. DNA was extracted from saliva of 49 child participants between 1 and 4 years old and is undergoing whole-genome bisulfite sequencing. Outcomes are percent DNAm, both genome-wide and at genomic regions related to energy regulation or fat deposition. Prenatal exposures were measured by the Geospatial Research, Analysis, and Services Program (GRASP) Place & Health burden percentile ranking, based on census tract of residence during pregnancy, with higher percentiles indicating greater burden. We will use regression to model associations of percent DNAm at gene loci of interest on GRASP percentile, controlling for relevant covariates (e.g., age, sex). Results/Anticipated Results: Final data collection, cleaning, and analysis are in progress and on target to be completed in Fall 2025. We will present final results of these analyses, including descriptive characteristics of the sample (e.g., summary and frequency statistics) and overall DNA methylation patterns (e.g., b or M values as appropriate), and whether there is support for our hypotheses that children with greater prenatal family and community exposures will have DNAm in pertinent genomic regions related to energy regulation or fat deposition (e.g., regression parameters and confidence intervals). Discussion/Significance of Impact: Findings will advance knowledge of early-life physiologic effects of exposures during pregnancy. Future clinicians may use this knowledge to earlier identify and treat children at high risk for adverse child metabolic health outcomes such as obesity, and health advocates can use it to promote policies to reduce adverse prenatal environments.

Objectives/Goals: The NIH Office of Data Science and Strategy created Data COUNTS (Collect Once, Use Numerous TimeS) to transform real-world data into actionable insights for translational research. The NEurOinformatics Network (NEON) applies this principle with neurology and national cohort use cases. Methods/Study Population: UNMC and Nebraska Medicine are deploying Data COUNTS to standardize data capture, ensure interoperability, and maximize reuse across research, clinical care, and operations. Teams integrate electronic health records, neuroimaging, biomarkers, wearable sensors, and social drivers of health into federated pipelines. HL7 FHIR and the OMOP Common Data Model maintain interoperability and reproducibility. Use cases include neurological disorders (multiple sclerosis, Alzheimer’s disease, and Parkinson’s disease), cancer outcomes through SEER, diabetes, and rural health disparities. Integration with the National Clinical Cohort Collaborative (N3C) leverages anchor variables and harmonized pipelines to connect local and national datasets for generalizable analytics and collaborative science. Results/Anticipated Results: By linking with CTSA, IDeA-CTR, SEER, N3C, and other national health data, this initiative strengthens Learning Health System infrastructure, accelerates precision medicine, and advances population health. Beginning at NM and UNMC, the model will extend to regional systems, especially in rural and underserved areas. Use cases in neurology, cancer, diabetes, and rural health demonstrate local impact, while SEER and N3C provide scalable pathways for harmonization and national integration. Discussion/Significance of Impact: Nebraska’s leading health system generates multimodal datasets that, connected with SEER and N3C through Data COUNTS principles, enable predictive modeling, explainable AI, and digital twins. These use cases operationalize a scalable framework for translational science.

Objectives/Goals: To evaluate how integrating genomic risk scores with environmental pollutants, endocrine disruptor exposure, and lifestyle factors enhances predictive accuracy for breast and ovarian cancer, improving early-risk stratification and advancing equitable precision prevention among diverse female populations. Methods/Study Population: A secondary data analysis was conducted using publicly available datasets from the UK Biobank and NIH All of Us cohorts (n = 5,128 women aged 25–70). Polygenic risk scores (PRS) for breast and ovarian cancer were combined with environmental exposures (PM 2.5, endocrine disruptors) and lifestyle factors (BMI, alcohol intake, physical activity). Eligible participants had complete genomic, environmental, and behavioral data. Multivariate logistic regression and random-forest algorithms evaluated predictive performance and interaction effects. Prior frameworks (Garcia-Closas et al., JNCI, 2014; Dudbridge et al., Nat Genet, 2018) guided variable selection, data harmonization, and fivefold cross-validation to ensure generalizability across cohorts. Results/Anticipated Results: Models integrating genomic, environmental, and behavioral variables achieved an AUC of 0.87 for breast cancer and 0.83 for ovarian cancer, outperforming PRS-only models (AUC = 0.74, p < 0.001). Fine particulate matter (PM 2.5) exposure and elevated BMI showed significant interactions with BRCA1/2 and CHEK2 variants, amplifying risk by ~1.5–2.3×. Counties with lower environmental quality had 10.8 more breast cancer cases per 100,000 (Gearhart-Serna et al., Sci Rep, 2023). Integrating pollution and lifestyle metrics improved early-risk classification, calibration, and predictive equity across populations, reducing false negatives by 18% and highlighting actionable, low-cost prevention targets for global women’s health. Discussion/Significance of Impact: Integrating genomic, environmental, and behavioral data enhances precision-medicine accuracy for cancer risk assessment. This approach supports equitable prevention by accounting for modifiable exposures and social determinants, reframing cancer prevention through precision public health, and informing population-level screening policy.

Objectives/Goals: The main objective of this study was to determine if dietary supplementation with the iron-binding protein lactoferrin is able to reverse age-related brain proteomic changes in a heterogenous mouse model of aging, with implications for the modulation of age-related brain disease. Methods/Study Population: UM-HET3 mice of both sexes were aged to 6 months on control chow (Young Control, N=11) or 24 months (Old Control, N=12) on control chow or a diet supplemented with 12,000 ppm of bovine lactoferrin for 9.5 weeks before sacrifice (Old Lactoferrin, N=13). At sacrifice, brain cortex was collected. Cortex homogenate was analyzed through SomaLogic for 1,500 specific proteins relevant to brain aging. Differential expression analysis was run to analyze the age and treatment effect separately, with an adjusted p-value cutoff of 0.05 to reveal effects of age (young control vs old control) and treatment (old control vs old lactoferrin) separately. Gene Ontology Biological Processes (GO-BP) Enriched Pathway analysis was run to identify the biological pathways altered by lactoferrin supplementation. Results/Anticipated Results: Differential expression analysis adjusted by sex identified 71 differentially expressed proteins in the age comparison and 99 differentially expressed proteins in the treatment comparison. Thirteen proteins were differentially expressed in both lists, which we classify as lactoferrin rescued proteins, those that were elevated in old untreated mice, but significantly lowered by treatment. These proteins include SYDC, CLIC5, NF2L2, STAT3, Peroxiredoxin.3, UFM1, Profilin.1, NUCB1, Laminin.2, Ezrin, PPT1, IDH, and PUR9. Pathway analysis revealed significant alteration in 30 pathways relevant to synapse, neuron, and cellular structure and function relevant to age-related neurodegenerative disease. Discussion/Significance of Impact: Lactoferrin may be a viable therapy for the modulation of age-related brain changes. Next, we will evaluate endogenous levels of lactoferrin as a biomarker for Alzheimer’s disease, moving toward a clinical trial to evaluate the utility of lactoferrin to serve as both a biomarker and intervention against age-related neurodegenerative disease.

Objectives/Goals: To identify barriers to HPV vaccination and cervical cancer screening among Black and Hispanic women in Northwest Louisiana as a first step toward developing community-driven strategies to eliminate cervical cancer in the state. Methods/Study Population: This cross-sectional study includes women aged 18–45 years who identify as Black or Hispanic. Participants are recruited through multiple methods, including community health fairs, churches, clinics, and snowball recruitment through peer referrals. Surveys are administered via REDCap in English and Spanish. We plan to enroll 260 women; this preliminary analysis includes 70. Structured surveys collect data on HPV awareness, provider offer, vaccination history, and cervical cancer screening. Sociodemographic characteristics and access factors are analyzed to describe prevention gaps. The study was approved by the LSUHS IRB (#00002755). Results/Anticipated Results: Preliminary findings reveal major prevention gaps. Nearly half (46%) had never heard of HPV, and 43% had never heard of the HPV vaccine. Among those aware, 59% reported never being offered the vaccine, and 76% had never received it. While 69% believed the HPV vaccine prevents cervical cancer and 21% said it prevents genital warts, nearly half (49%) were unsure about its effectiveness. Among mothers, 31% were willing to vaccinate their children, and 7% had already done so. For cervical cancer screening, 86% had a Pap test; however, 20% were not up to date. Among those screened for cervical cancer, most reported their last test was over three years ago. Participants were on average 33.2 years old (SD = 8.1), predominantly Black (74%) or Hispanic (26%), with 57% single, 66% employed full-time, and 72% insured. Discussion/Significance of Impact: Eliminating cervical cancer in Louisiana requires equitable access to HPV vaccination and screening. This study identifies important prevention gaps in minority women and demonstrates how community-based approaches can inform targeted interventions to achieve cervical cancer elimination.

Objectives/Goals: The objective of this study was to identify the support needs of faculty conducting health-related community engaged research (CEnR) at the University of Michigan (U-M). Our primary goal was to develop a faculty-informed needs assessment survey. Methods/Study Population: We conducted semi-structured interviews with seven U-M faculty members engaged in health-related CEnR. Participants were affiliated with the Michigan Institute for Clinical and Health Research (MICHR), represented a variety of health disciplines, and had varying levels of CEnR experience. Interviews explored research processes, challenges, and support needs. Transcripts were thematically analyzed. Findings informed the design of a university-wide needs assessment survey, to be distributed to ~1,000 faculty conducting health-focused CEnR across all three of U-M’s campuses. This formative qualitative study represents the initial phase of a broader, mixed-methods effort to strengthen institutional support for translational research through community engagement. Results/Anticipated Results: Interviews revealed key needs across the CEnR lifecycle from study design, partnership development, project management, and dissemination. Themes included the value of introductions to communities by trusted faculty, challenges sustaining partnerships between funding cycles, and the need for greater recognition of CEnR in promotion and tenure. These insights directly shaped the needs assessment survey, which aims to validate and expand on these themes. Findings from the survey will inform CE Team priorities, guide service development, and address barriers that limit the effectiveness and impact of community-engaged translational research at U-M. Discussion/Significance of Impact: By centering faculty voices, this work ensures future programming and services are aligned with real-world needs. Strengthening institutional support for CEnR will improve the systems, methods, and process that enhances its effectiveness and impact, accelerating research translation and fostering stronger university-community partnerships.

Objectives/Goals: Rare pediatric cancer research has been hindered by limited sample size and disease-specific databases. The training and infrastructure required to create these datasets have been cost prohibitive. Automated electronic medical record (EMR) extraction and natural language processing (NLP) hold the potential to overcome these limitations. Methods/Study Population: In a mixed population of adults and children with thyroid cancer, we implemented an automated data extraction process for multiple data types, including structured demographic, laboratory, and billing data and unstructured free text from pathology reports. Data extraction and cleaning software transformed EMR data into a research-ready database. NLP using regular expressions extracted meaningful, structured data from free-text pathology reports. Results from the automated data extraction and NLP were compared to manual extraction, and results were quantified using accuracy, precision, recall, F1-score, and Cohen’s Kappa to account for random agreement. Additional iterations using machine learning and large language models will be performed to compare accuracy and identify an optimal strategy. Results/Anticipated Results: From 2016 to 2023, 2,899 patients with thyroid cancer were identified. In a 50-patient subset, manual extraction of pathology reports was compared to NLP-derived data. Histology type was correctly identified in 90% of cases (kappa = 0.85), and thyroid procedure identification accuracy was 89% (kappa 0.81). Focality was 98% accurate (kappa=0.96). Vascular, lymphatic, and perineural invasion, along with extrathyroidal extension and pathologic tumor stage, were 100% accurate. Pathologic nodal staging was 96% accurate (kappa=0.89). Kappa greater than 0.8 is considered almost perfect agreement. Discussion/Significance of Impact: Our results indicate that automated EMR extraction and NLP can be used to develop a thyroid cancer dataset that is highly detailed, accurate, and efficient to collect. After optimizing our system of data extraction, we will replicate this process in a multi-center study with the eventual goal to expand these algorithms across rare pediatric cancers.

Objectives/Goals: Although the Deepest Vertical Pocket (DVP) method is increasingly used to assess amniotic fluid volume due to its simplicity and lower intervention rates, its relationship with neonatal outcomes remains underexplored. This study aims to determine if DVP measurements are associated with Apgar scores at 1 and 5 minutes in low-risk term pregnancies. Methods/Study Population: An IRB-approved retrospective cohort study of 171 singleton term pregnancies delivered at Penn State Hershey Medical Center between 2019 and 2024 was performed. Inclusion criteria included delivery at ≥37 weeks, birth weight between the 10th and 90th percentiles, absence of fetal anomalies, spontaneous labor or scheduled Cesarean, and classification as low risk based on ACOG 2019 Levels of Maternal Care guidelines. A single second-trimester DVP measurement was obtained from anatomy ultrasounds. Apgar scores at 1 and 5 minutes were abstracted from delivery records. Statistical analysis included ANOVA and Spearman correlation to assess relationships between DVP and Apgar scores. Results/Anticipated Results: Among 171 patients, the mean DVP was 4.79 cm (SD 0.94). Apgar scores at 1 minute were most commonly 8 (73%) or 9 (15%), and 94% of neonates had a score of 9 at 5 minutes. There was no statistically significant correlation between DVP and Apgar scores at 1 minute (Spearman r = –0.11, p = 0.14) or 5 minutes (r = 0.10, p = 0.19). ANOVA results also revealed no significant differences in DVP across Apgar score categories at 1 minute (p = 0.12) or 5 minutes (p = 0.41). Discussion/Significance of Impact: In this cohort of low-risk term pregnancies, DVP was not significantly associated with Apgar scores at 1 or 5 minutes. This study is one of the few to isolate DVP rather than AFI and to apply it to routine obstetric care. These findings support the use of DVP as a non-invasive, reliable fluid assessment method without concern for adverse neonatal outcomes.