Objectives/Goals: Predictive performance alone may not determine a model’s clinical utility. Neurobiological changes in obesity alter brain structures, but traditional voxel-based morphometry is limited to group-level analysis. We propose a probabilistic model with uncertainty heatmaps to improve interpretability and personalized prediction. Methods/Study Population: The data for this study are sourced from the Human Connectome Project (HCP), with approval from the Washington University in St. Louis Institutional Review Board. We preprocessed raw T1-weighted structural MRI scans from 525 patients using an automated pipeline. The dataset is divided into training (357 cases), calibration (63 cases), and testing (105 cases). Our probabilistic model is a convolutional neural network (CNN) with dropout regularization. It generates a prediction set containing high-probability correct predictions using conformal prediction techniques, which add an uncertainty layer to the CNN. Additionally, gradient-based localization mapping is employed to identify brain regions associated with low uncertainty cases. Results/Anticipated Results: The performance of the computational conformal model is evaluated using training and testing data with varying dropout rates from 0.1 to 0.5. The best results are achieved with a dropout rate of 0.5, yielding a fivefold cross-validated average precision of 72.19% and an F1-score of 70.66%. Additionally, the model provides probabilistic uncertainty quantification along with gradient-based localization maps that identify key brain regions, including the temporal lobe, putamen, caudate, and occipital lobe, relevant to obesity prediction. Comparisons with standard segmented brain atlases and existing literature highlight that our model’s uncertainty quantification mapping offers complementary evidence linking obesity to structural brain regions. Discussion/Significance of Impact: This research offers two significant advancements. First, it introduces a probabilistic model for predicting obesity from structural magnetic resonance imaging data, focusing on uncertainty quantification for reliable results. Second, it improves interpretability using localization maps to identify key brain regions linked to obesity.

Objectives/Goals: Objective: To examine whether familial longevity modifies the relationship between chronic kidney disease (CKD) and cardiovascular disease (CVD) in older adults. Goals include assessing the impact of familial longevity on 1) CVD prevalence, 2) CVD incidence, and 3) mortality among individuals with CKD. Methods/Study Population: An observational, longitudinal study. We examined 1,236 Ashkenazi Jewish adults (ages 65–94) from the LonGenity cohort. Estimated glomerular filtration rate (eGFR) was the independent variable, calculated using the CKD-EPI equation 2021. CVD prevalence, incidence, and mortality were our outcomes. CVD was defined as a composite of MI, PCI, CABG, or stroke. Exceptional longevity was defined as living past 95 years, grouping participants into OPEL (offspring of parents with exceptional longevity, n = 576) and OPUS (offspring of parents with usual survival, n = 604). Stratified logistic regression and Cox proportional hazards models assessed eGFR’s association with CVD, testing effect modification through eGFR × OPEL interaction terms. Median follow-up was 5.5 years. Results/Anticipated Results: A significant association was observed between eGFR and CVD prevalence in OPUS, but not in OPEL. No significant link was found between eGFR and CVD incidence or mortality in either group. Familial longevity did not modify the association between eGFR and CVD prevalence, nor the composite of CVD incidence and mortality, as the interaction term was nonsignificant. The LonGenity cohort’s health status may have influenced these results due to selection and survivor biases, limiting generalizability. Further research is needed to clarify familial longevity’s role in kidney function and cardiovascular outcomes. Discussion/Significance of Impact: Our findings suggest that kidney function, as measured by eGFR, may be associated differently with cardiovascular risk in those with and without familial longevity. The study highlights potential limits of familial longevity in modifying CVD risk associated with CKD, underscoring the need for tailored CVD prevention strategies.

Objectives/Goals: Accurately stratifying patients with clinically isolated syndrome by risk of developing multiple sclerosis is of great clinical importance. Though numerous prediction models attempt to achieve this goal, no systematic review exists to independently evaluate these models. We aim to systematically identify and assess the risk of bias in all such models. Methods/Study Population: Studies developing or validating prediction models to assess risk of developing MS in patients with CIS who are not receiving an MS-indicated disease-modifying therapeutic will be identified via a systematic literature search. Studies will be evaluated for overall risk of bias using PROBAST (Prediction model Risk Of Bias Assessment Tool). Briefly, data sources, predictor, and outcome definition and assessment, applicability, and analysis will be assessed for each model in each identified study, and an overall risk of biased judgment will be assigned. Identified studies, predictors incorporated, results, and risk of bias assessment with accompanying rationale will be summarized in the final report. Results/Anticipated Results: Based on an initial exploratory search, we anticipate that most, if not all, identified prediction models will have high risk of bias. We anticipate that many studies will have limited applicability due to the use of outdated diagnostic criteria for definition of outcomes, or high risk of bias concerns originating from their analysis due to insufficient volume of included participants or poor model validation practices. We further anticipate that most, if not all, of the identified prediction models will have limited potential to be translated to use in a clinical setting. Discussion/Significance of Impact: Understanding how to identify patients with high-risk CIS may inform and improve clinician treatment decisions, patient outcomes, and future research study design. This work may also reveal flaws in current prediction models for CIS, opening new avenues of research and prompting development of improved prognostic models for patients with CIS.

Objectives/Goals: With qualitative interviews we aim to 1-Describe barriers and facilitators for post-transplant lymphoproliferative disease (PTLD) survivors’ access to late effects (LE) care. 2-Investigate clinicians’ perceptions of current and ideal PTLD LE care. Our long-term goal is to develop and pilot implementation strategies to standardize PTLD LE care. Methods/Study Population: Study population: We will recruit 20–25 PTLD survivors or their caregivers and 10–15 health care workers (HCW) from oncology, LE, and solid organ transplant (SOT) teams at St. Louis Children’s Hospital (SLCH). PTLD is a lymphoma-like cancer that occurs in solid organ transplant (SOT) recipients. PTLD survivors experience LE from cancer, yet many do not receive LE care. Research strategy: We will conduct qualitative semi-structured interviews based on the Consolidated Framework for Implementation Research (CFIR). A preliminary codebook will be based on CFIR and refined through transcript review. Team-based coding includes double coding and checking for intercoder reliability. We will generate coding reports to understand themes and identify barriers and facilitators of LE care. Results/Anticipated Results: We hypothesize survivors, caregivers, and HCWs will identify actionable factors to inform future studies to optimize LE care. We will examine the CFIR inner setting (resources, communication, and structural characteristics), outer setting (local attitudes and external pressures), innovation domain (adaptability, evidence base, and relative advantage), individuals domain (need, opportunity, and motivation), and implementation process domain. Our contribution will be novel. 1-This is the first assessment of barriers and facilitators for LE care in pediatric PTLD survivors. 2-We will consider input from HCWs across various disciplines delivering care to PTLD survivors. 3-We anticipate identifying unique contextual factors in PTLD survivors that will influence implementation of evidence-based LE care. Discussion/Significance of Impact: Pediatric cancer survivors experience LE. Coordinated care mitigates LE. PTLD survivors experience a high burden of LE, but less than 10% of PTLD survivors at SLCH follow in LE clinic. No studies have evaluated ideal delivery of LE care for PTLD survivors. Our findings will inform an implementation trial to improve delivery of LE care for PTLD survivors.

Objectives/Goals: Global surgical education is largely driven by high-income countries (HICs), with curricula not tailored to the needs of low- and middle-income countries (LMICs). This study assessed country-specific needs for global surgical curricula and used generative AI to develop tailored curricula. Methods/Study Population: A curriculum framework was developed using expert opinion. Using a focused needs assessment survey, we evaluated international medical students’ and trainees’ needs for structured global surgery curricula, covering research, education, data and develop tailored curriculum templates for each country, ensuring alignment with the distinct needs of respective LMIC and HIC respondents. The AI-generated curricula were then compared across countries to identify variations in content and focus areas. Results/Anticipated Results: A total of 145 respondents from 18 countries and 6 continents participated, with 94 from LMICs and 51 from HICs. Four countries [Uganda (n = 31), Nigeria (n = 34), the USA (n = 23), and the UK (n = 23)] had more than 10 respondents, with the creation of a country specific global surgery curriculum. Curricula developed by HIC trainees focused on access to resources and infrastructure, future directions of global surgical research, and the role of medical students and early career development with a decreased focus on the history of global surgery. LMIC country-based curriculum focused on introducing the concepts of global surgery, quantifying the burden and epidemiology of surgical disease and had a greater emphasis on case studies and use cases, with decreased focus on resources and collaboration. Discussion/Significance of Impact: The research introduces a “precision education” approach that could help close the surgical education access gap globally. Further pilot and qualitative studies are necessary to validate the feasibility of AI-generated needs-based curricula.

Objectives/Goals: Cerebral amyloid angiopathy-related inflammation (CAA-ri) is a spontaneous inflammatory cerebral vasculopathy that mimics complications of Alzheimer’s disease immunotherapies. Our objective is to evaluate imaging and cerebrospinal fluid (CSF) markers of blood–brain barrier (BBB) impairment and inflammation in CAA-ri. Methods/Study Population: We plan to enroll 20 patients total: 1) 10 patients with CAA-ri as defined by Auriel et al (JAMA Neurology 2016) (exposure group). 2) 10 patients with non-inflammatory CAA defined using Boston criteria 2.0 that do not also meet criteria for CAA-ri (control group). The primary outcome will be Ktrans, a parameter of BBB impairment calculated from dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) of the brain. Secondary outcomes will include DCE-MRI parameter VL, CSF albumin index, CSF fibrinogen, CSF sPDGFR-β, CSF MMP-2, CSF MMP-9, CSF C3, CSF IL1β, CSF IL6, IL8, and TNFα. Statistical comparisons between the exposure and control groups will be made using Wilcoxon rank sum test. Results/Anticipated Results: We anticipate significantly higher levels of BBB impairment and inflammatory biomarkers from DCE-MRI and CSF in subjects with CAA-ri relative to control subjects with non-inflammatory CAA. Discussion/Significance of Impact: Biomarkers are essential to characterize risk factors, pathophysiology, and possible treatment targets in CAA-ri. We plan to use the results of the current study to inform longitudinal studies that will test whether these markers are useful in identifying not only the presence of CAA-ri but also severity, progression, and response to treatment.

Objectives/Goals: A sample of 1,073 hypertensive adults in Bangladesh showed unusually high rates of hypokalemia. We analyzed sociodemographic and clinical factors – including age, sex, weight, body mass index, blood pressure, creatinine clearance, and urine protein concentration – to identify key predictors of hypokalemia. Methods/Study Population: A cross-sectional analysis was conducted on 1,073 hypertensive adults from the OK study in Dhaka, Bangladesh (2022–2023). Hypertension was defined as blood pressure >140/90 mmHg, and none of the participants were on any antihypertensive medication prior to the study. Hypokalemia was defined as serum potassium Results/Anticipated Results: The prevalence of hypokalemia was 21.5%. In univariate analysis, age (OR 0.975, 95% CI [0.959, 0.990], p  =  0.00189), systolic blood pressure (OR 1.02, 95% CI [1.00, 1.03], p  =  0.00568) and diastolic blood pressure (OR 1.03, 95% CI [1.01, 1.04], p  =  0.000272) were significantly associated with hypokalemia. In multivariate analysis, age (OR 0.961, 95% CI [0.936, 0.985], p  =  0.00167) remained significant, and creatinine clearance (OR 0.986, 95% CI [0.974, 0.999], p  =  0.0386) became significant. BMI, weight, systolic and diastolic blood pressure, sex, and urine protein concentration were not significant. Discussion/Significance of Impact: In the multivariate analysis, age and creatinine clearance was statistically significant; however, their effect sizes were small and unlikely to be clinically meaningful. The underlying reasons for the high prevalence of hypokalemia in this population remain unclear, warranting further investigation to identify contributing factors.

Objectives/Goals: Increased follicle-stimulating hormone (FSH) is linked to declines in ovarian and metabolic function in older women. Obesity is both a manifestation and a driver of aging pathologies. In animal models, FSH and insulin resistance (IR) were reduced after 6 mos. of a nutritional therapeutic (GLYLO). Our goal was to translate preclinical evidence to humans. Methods/Study Population: An integrated, precision medicine approach identified a unique phenotype of aging-related debility relative to older females. A non-comparer pilot study was conducted to translate GLYLO preclinical findings to postmenopausal women with obesity (n = 85; >55 years; body mass index [BMI]  = 35.0±4.35; range: 30.3–42.8). Participants meeting the inclusion and exclusion criteria (n = 13) were enrolled and received two capsules of GLYLO (vitamins and natural products) daily for 6 mos. Assessments for FSH, estradiol (E2), IR (homeostatic model [HOMA-IR]), total cholesterol (TC), low- (LDL), high-density lipoproteins (HDL), safety biomarkers (e.g., red cell distribution width [RDW%], mean corpuscular volume [MCV]), and depression (Center for Epidemiologic Studies Depression Scale) were conducted prior to and after 6 mos. Results/Anticipated Results: Mixed-effect models with intent-to-treat analysis were applied to compare outcomes prior to (n = 13) and following (n = 7) the intervention. Significant reductions in FSH were observed (-13.1 [2.47] ∆/SD; p = 0.002)) following the 6-month intervention. Interestingly, BMI, E2 (p = 0.412), HOMA-IR (p = 0.885), TC (p = 0.363), and LDL (p = 0.145) were unchanged, while HDL decreased significantly (-9.7 [3.82] ∆/SD; p = 0.044). Other biomarkers, RDW% (-0.2 [0.05] ∆/SD; p = 0.009) and MCV (-2.3 [0.33] ∆/SD; p = 0004), were significantly reduced. All other safety parameters were not altered. Six participants reported mild to moderate adverse events (acid indigestion) and were lost to follow-up. Depression scores significantly increased (+4.0 [0.75] ∆/SD; p = 0.002)). Results were similar with and without intent to treat analysis. Discussion/Significance of Impact: Decreased FSH, but not IR, was observed following six months of GLYLO in postmenopausal women with obesity. Significant alterations in HDL, depression, RDW%, and MCV warrant further investigation. Findings are limited by the small sample size and loss to follow-up. Randomized, controlled trials are needed to confirm these results.

Objectives/Goals: The purpose of this study was to document the publicly available literature, measurement tools, secondary data, and expert perspective on the intersectional care gaps and disparities of children with palliative needs in foster care. Methods/Study Population: Four data collection methods determined the frontier of available information on the palliative needs of children in foster care. A literature review assessed the quality and content of published evidence. A catalogue of relevant measures tools and validation results determined what psychometric tools exist for the population, how well they performed in validation studies, and if any incorporated community members in their development. The National Data Archive for Child Abuse and Neglect was consulted to assess whether existing secondary data was fit for purpose. Informal interviews will be conducted with subject matter experts (pediatrics, palliative care, foster care) to determine the legitimacy and urgency of the problem. Results/Anticipated Results: Health inequities among children in foster care and children with medical complexity (CMC) suggest a strong likelihood of unmet palliative care needs for CMC in foster care; however, no literature or data describe the scope and severity, and few insights support development of safe and supportive interventions to meet these needs. No national publicly available datasets include both foster-related case or placement information and diagnosis or service-specific data, including Medicaid data and the Adoption and Foster Care Analysis and Reporting System (AFCARS). No work has been published integrating foster parents or former foster youth input on palliative needs. Participatory action research methodologies with critically ill patients have led to improvements in patient experience and clinical care. Discussion/Significance of Impact: The lack of data, community engagement, and validated measures to identify palliative needs of children in foster care stymie efforts to identify and correct health inequities. Participatory action research is needed to meaningfully engage foster and health care partners to determine what palliative care needs should be prioritized and measured.

Objectives/Goals: As life expectancy increases in people with HIV, neurocognitive impairment is becoming more common, and women with HIV (WWH) are disproportionately impacted. This work investigated mitochondrial function and oxidative stress in WWH in order to understand the relationship between mitochondrial function and cognition in future studies. Methods/Study Population: Peripheral blood mononuclear cells were isolated from virally suppressed WWH (n = 64) and underwent the Seahorse Cell Mito Stress test to assess different realms of mitochondrial function. Cells were then lysed for direct DNA extraction, and quantitative PCR was performed to understand mitochondrial DNA expression (mtDNA) levels as a measure of oxidative stress. A series of simple linear regressions was then conducted to understand the relationships between mitochondrial function and mtDNA content. Future work will expand this analysis to investigate associations between demographic dynamics, such as trauma history, and mitochondrial function, as well as to understand the relationships between mitochondrial function and cognitive outcomes in WWH. Results/Anticipated Results: In our cross-sectional analysis of mitochondrial dynamics in WWH, we found a significant association between maximum mitochondrial respiration ability and mtDNA content, with greater mtDNA expression associated with increased levels of maximum respiration following stimulation. There was no association between basal respiration and levels of oxidative stress. There was also a significant variation in mitochondrial function in our participants, indicating that future analyses to investigate the source of that variation are warranted. The work presented here sheds light on mitochondrial dynamics in WWH and will be the basis for future studies that will investigate how demographic dynamics may be associated with mitochondrial function, as well as how mitochondrial dynamics may predict cognitive outcomes. Discussion/Significance of Impact: There is significant variation in mitochondrial function in WWH. More analysis is needed to understand what may be associated with these variations, including an investigation of both clinical factors as well as cognitive outcomes. This analysis will inform directions for future mechanistic work aimed at mitigating adverse cognitive outcomes in WWH.

Objectives/Goals: Physical activity (PA) is a well-documented protective factor against many cardiovascular diseases. PA guidelines to reduce these risks and the impact of variability are unclear, and most studies only examine a 7-day activity window. This study aimed to examine factors related to variability in step counts in a 3-year study of adults aged ≥18 years. Methods/Study Population: Included were 6,525 participants from the Michigan Predictive Ability and Clinical Trajectories study, a prospective cohort of community-dwelling adults enrolled between 8/14/2018 and 12/19/2019 who received care at Michigan Medicine and were followed for 3 years. Data were collected from Apple Watches provided to participants via the HealthKit. This secondary analysis included those with ≥4 valid weeks of data (≥4 days with at least 8 hours of wear time). Season was defined as Spring (March 20–June 20), Summer (June 21–September 21), Fall (September 22–December 20), and Winter (December 21–March 19). GEE models against the outcome of variability, defined as weekly standard deviation of step counts, and the predictor of season were adjusted for age, sex, race/ethnicity, weekly average step count, diabetes, and body mass index. Results/Anticipated Results: The average (standard deviation (SD) step counts by season were 7101 (3434) in Spring, 7263 (3354) in Summer, 6863 (3236) in Fall, and 6555 (3211) in Winter. Compared to winter, there was statistically significantly higher variability in all other seasons (p Discussion/Significance of Impact: In this cohort of community-dwelling adults, we found significant differences in variability of physical activity by season, age, and BMI. Future work will examine how this variability impacts the risk of development of cardiovascular disease, incorporating the impact and recovery trajectories of COVID-19 and other acute respiratory infections.

Objectives/Goals: Acute myeloid leukemia (AML) is the second most common leukemia among pediatric populations. Approximately 15% of pediatric AML cases have KMT2A gene rearrangements (KMT2A-r), which confers a worse prognosis. Our goal is to better characterize the biologic landscape of KMT2A-r pediatric AML. Methods/Study Population: This study utilizes deidentified peripheral blood and/or bone marrow samples banked in the Children’s Mercy Tumor Bank Biorepository. We investigated four KMT2A-r pediatric AML patients and six patients with other AML subtypes using samples collected at diagnosis and remission that were stored in the “tumor bank.” In addition, we assessed 47 tumor bank samples from patients with other leukemia subtypes. We performed differential expression (DE) analysis on bulk RNA sequencing comparing KMT2A-r and all other AML subtypes, as well as single-cell RNA sequencing and proteomic analysis on the larger cohort. We then coalesced these data to better identify processes and pathways that are dysregulated in KMT2A-r AML, specifically aiming to find those that were contributing to leukemogenesis. Results/Anticipated Results: Transcriptomic analysis showed that HOXA10 and MEIS1, two genes associated with immature myeloid populations and KMT2A-r leukemias, were more highly transcribed in AMLs than other leukemias. In addition, our DE analysis showed significantly higher transcription of ITGA7, a gene shown to correlate with poorer prognosis in AML, in our KMT2A-r samples when compared to other AML subtypes. FAM46C, a tumor suppressor gene contributing to mRNA stabilization, was less highly expressed in KMT2A-r AML when compared to other AML subtypes. Of note, low expression of FAM46C is associated with poorer survival and treatment response in multiple myeloma, and our findings suggest it may also be relevant to AML. Proteomic analysis is currently in process. Discussion/Significance of Impact: Transcriptomic analysis identifies unique molecular features of pediatric KMT2A-r AML. We anticipate that our proteomic data will do the same and will also corroborate our RNA findings. Taken in combination, these results will provide a more complete picture of the specific mechanisms contributing to this aggressive leukemic subtype.

Objectives/Goals: Youth with IBD have preventive, psychosocial, and acute care needs beyond those of peers, yet receipt of services does not match those needs. Our objectives are to assess the feasibility of (1) an individualized care plan intervention to improve perceived and measured care quality and (2) a pragmatic trial design embedded in pediatric IBD practice. Methods/Study Population: This is a pilot rollout-design randomized trial (n = 60) at a regional academic medical center. Eligible patients are 13–19 years old with IBD for at least 3 months and scheduled for a follow-up visit during the trial. Research staff recruits from one cluster at a time until goal enrollment (14–16). Enrollees are randomized 1:1 to intervention (MyIBD now) or control (MyIBD after the trial). MyIBD combines a tabular summary of individualized acute, chronic, and preventive care needs with nurse facilitator support for patients to use the information. Surveys at baseline, 6 and 12 months measure care quality (Patient Assessment of Chronic Illness Care scale, vaccines, health services) and patient self-management skills (Partners in Health scale). Implementation outcomes are collected via chart review. Results/Anticipated Results: To date, 44 subjects have been randomized. Among subjects, the mean age is 16 years; 73% have Crohn’s disease, 77% have commercial insurance, 75% receive anti-TNF therapy, and 14% live in a rural area. Mean baseline perceived care quality (PACIC scale) is 76.9 (sd 16.3; out of 100); mean baseline perceived self-management skill (PIH scale) is 78.1 (sd 13.4; out of 96). On objective care quality measures, 59% have completed the HPV vaccine series, 32% have received an additional pneumonia vaccine; in the past year 68% have had a screening for mood disorders, 20% an emergency department visit for IBD, and 18% an IBD hospitalization. To date, the IBD clinical team has achieved 100% completion (intervention subjects receive MyIBD plus nurse facilitation) and 0% contamination (control subjects inappropriately receive MyIBD). Discussion/Significance of Impact: Study results to date support the feasibility of the pragmatic, embedded trial design and indicate opportunities for improvement in care quality as perceived by patients and as measured by common preventive and acute care quality indicators. An individualized care plan supported with nurse facilitation may improve pediatric IBD care quality.

Objectives/Goals: Sexual minority populations report a disproportionately high prevalence of alcohol use, often attributed to coping with bi/homonegativity and systemic inequities across various social domains. This study aims to explore alcohol use patterns and associated neighborhood and individual factors among sexual minority populations (SMPs) using data from the NIH All of US dataset. Methods/Study Population: Alcohol use was assessed using the AUDIT-C (Alcohol Use Disorders Identification Test—Consumption) scale across a sample of 9,454 gay, 15,284 bisexual, 5,267 lesbian, and 349,748 straight participants. The AUDIT-C measured hazardous alcohol use, and logistic regression models were employed to examine its association with neighborhood-level factors (e.g., socioeconomic status, alcohol outlet density) and individual-level factors (e.g., age, race/ethnicity, income, and education) among SMPs. Interaction terms assessed how these relationships varied by sexual orientation. Sensitivity analyses were conducted to assess the robustness of the findings, including stratified analyses by gender identity and the exclusion of extreme outliers in alcohol use reporting. Results/Anticipated Results: Our analyses revealed that gay participants had the highest AUDIT-C scores (mean  =  3.60, SD  =  2.27), followed by bisexual (mean  =  3.35, SD  =  2.21), other SMPs (mean  =  3.18, SD  =  2.19), lesbian (mean  =  3.04, SD  =  2.08), and straight individuals (mean  =  3.05, SD  =  2.06). Alcohol use was positively associated with neighborhood disorder (β  =  0.12, 95% CI  =  0.07, 0.17), housing insecurity (β  =  0.14, 95% CI  =  0.03, 0.25), and male gender (β  =  0.98, 95% CI  =  0.96, 1.00). In contrast, neighborhood density (β  =  -0.11, 95% CI  =  -0.15, -0.07), food insecurity (β  =  -0.14, 95% CI  =  -0.20, -0.08), being Black, and identifying as bisexual were negatively associated with alcohol use. Sensitivity analyses determined no significant differences among specfic supgroups. Discussion/Significance of Impact: This study highlights important differences in alcohol use across SMPs and emphasizes the influence of neighborhood-level stressors (e.g., disorder and housing insecurity). These findings underscore the need for addressing social and environmental determinants of alcohol use in SMPs to mitigate the negative impacts of alcohol consumption.

Objectives/Goals: As translational science (TS) emerges as a field, there is a need for research organizations to understand how to develop capacity for and support the advancement of TS. To support such institutional and infrastructural change, this poster outlines a Translational Science Promotion and Research Capacity (T-SPARC) framework. Methods/Study Population: The T-SPARC framework was developed by members of the Duke University Clinical and Translational Science Institute (CTSI) primarily from CTSI Pilots, Team Science, Evaluation, and Administration, all of whom had identified the need for building institutional capacity for TS at our institution. The group reviewed literature on TS to ensure grounding in current knowledge, drafted an initial TS logic model, and then determined the value of developing a framework addressing building TS institutional capacity. The group then identified other frameworks/models related to behavioral, organizational, and system change; examined scholarship addressing the building of research capacity in colleges and universities; and iterated on a TS-focused framework in multiple working sessions. Results/Anticipated Results: The resultant T-SPARC framework provides a foundation to 1) inform the development of interventions and programs advancing TS and 2) evaluate their effectiveness. It outlines: organizational levels for TS capacity building (large-scale systems, research institutions, teams, and individuals); intervention activities (policies and processes, funding, collaboration and partnership, and training); proximal outcomes (knowledge/attitudes, behaviors, resources/infrastructure, and connections); next-stage outcomes (e.g., interdisciplinary team processes, and research infrastructure); and ultimate goals (fewer translational impediments, improved public health, and health equity). It ingrates TS principles as foundational to, and outcomes of, capacity-building efforts. Discussion/Significance of Impact: T-SPARC, as a framework for building capacity in TS, provides added foundation for advancing the conceptualization and practice of TS. Ultimately, T-SPARC seeks to advance broader goals of reducing longstanding challenges in the translational research process and improving health outcomes.

Objectives/Goals: The never in mitosis kinase (NEK) family regulates vital processes, namely cell cycle progression, but their potential as therapeutic targets in TNBC has not been fully explored. Our studies aim to develop a toolkit to investigate the functional roles of NEKs in pathologies including carcinogenesis. Methods/Study Population: To assess differential NEK expression in normal and tumor tissues and correlation of gene expression with patient survival, we used Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan–Meier Plotter (KMPlot) pan-cancer analysis, respectively. Basal NEK protein levels were determined by immunoblot across a panel of cell lines, including breast cancer, osteosarcoma, hepatocellular carcinoma, and non-cancerous cells, to identify appropriate systems for evaluation of NEK function. Doxycycline-inducible cell lines were generated by transduction with lentiviral stocks of NEK shRNA and overexpression constructs and antibiotic selection. Expression was analyzed by qPCR and immunoblot. Results/Anticipated Results: Expression of NEK2, 4, 5, 6, 8, and 11 was higher in breast tumors compared to normal tissue by GEPIA analysis. Further examination using KMPlot showed a correlation between elevated NEK6 expression and decreased overall survival in patients with aggressive cancers. As an initial proof-of-concept study, we analyzed NEK6 protein expression in breast cancer cells. Levels of NEK6 were elevated in TNBC cells (MDA-MB-231) compared to hormone receptor positive (HR+) breast cancer cells (MCF7). Using complementary approaches to investigate the functional role of NEK6 in breast cancer, we depleted NEK6 expression using shRNAs in TNBC cells and expressed NEK6 in HR+ cells Discussion/Significance of Impact: Because kinase dysregulation promotes oncogenesis and metastasis, targeting kinases is a key strategy in therapeutic development. A NEK-specific molecular toolkit allows researchers to elucidate NEK functions and contributions to carcinogenesis, promoting advancement of novel therapies.

Objectives/Goals: The University of Minnesota’s two-year TL1 program provides flexible and individualized education and training for a diverse cohort of scholars committed to pursuing impactful careers in clinical and translational science (CTS). The program aims to strengthen the nation’s biomedical workforce by developing scientists skilled in clinical and translational research. Methods/Study Population: The TL1 program recruits PhD candidates and postdoctoral fellows from a wide variety of graduate programs in colleges and departments across the University. To date, we have trained 26 predoctoral and 9 postdoctoral Scholars in 3 cohorts. Scholars represent dozens of disciplines and the full translational spectrum. These interdisciplinary cohorts are in a unique position to realize the fundamental characteristics of a translational scientist. Entrance/exit surveys and exit interviews provide program leadership with information for quality improvement and areas scholars believe contribute the most to their education and training in CTS. Results/Anticipated Results: Entrance/exit surveys indicated Scholar-perceived benefits of training in an interdisciplinary program, including growth in translational scientist characteristics (e.g., Boundary Crosser, Team Player). Exit interviews showed Scholars appreciated the cohort model bringing together trainees from many different research areas. They valued exposure to varied perspectives, talking through challenges and solutions with each other, and learning others shared similar issues. They valued the Scholar community they developed. Several felt siloed in their careers before the program and reported that TL1 participation connected them to others outside their own area of focus, expanded their knowledge about different research methods and revealed more pathways for translation. Discussion/Significance of Impact: Recruiting and training a diverse interdisciplinary cohort of pre- and postdoctoral TL1 Scholars promoted synergy in translational research, science skills and competencies, and transformed the perspectives of Scholars’ views on the importance of interdisciplinary collaboration to accelerate science.

Objectives/Goals: The study is designed to co-develop a genetics education digital platform with community participants. Diverse populations, especially African American communities, are less likely to participate in genetic testing and clinical trials. To increase participation and community input, we want community participants across Louisiana. Methods/Study Population: A cross-sectional, mixed-methods study will be conducted to assess interest in learning about genetics through a digital education platform and to adapt the platform based on participant feedback. Specific Aim 1 will be achieved by recruiting a diverse cohort and collecting demographic data to identify participants’ characteristics. For Specific Aim 2, 35 community participants will be enrolled as a co-design team to complete 5-week educational modules. Feedback from focus groups will guide iterative platform refinements, ensuring the platform is culturally tailored and user-friendly. Results/Anticipated Results: For Specific Aim 1, we anticipate that the majority of participants will express interest in learning about genetics through the digital platform, with demographic data revealing a diverse participant pool, predominantly from African American and Hispanic communities. For Specific Aim 2, we expect that all 35 co-design team members will complete the 5-week modules. Feedback from the focus groups is anticipated to highlight the need for more user-friendly navigation, culturally tailored content, and enhanced visuals. These insights will guide the refinement of the digital platform for improved engagement and accessibility. Discussion/Significance of Impact: This study addresses a critical translational barrier – underrepresentation of African descended communities in genetic testing. By developing a culturally tailored, digital platform to engage these populations, the project aims to reduce health disparities, enhance genetic literacy, and foster inclusivity in genomic research.

Objectives/Goals: This study examines prevalence of complete sample size justifications in publications in the top five clinical neurology journals. Secondary goals include comparing study designs and clinical populations to explore whether some may be more likely to include inadequate sample size considerations. Methods/Study Population: Recent studies (n  =  125) in Lancet Neurology, Alzheimer’s and Dementia, JAMA Neurology, Acta Neuropathology, and Brain will be evaluated. For each journal, the 25 most recent empirical articles between 2022 and 2023 will be examined for their inclusion of a justification and reproducible sample size calculation. Inclusion of components of an ideal sample size justification will be evaluated: effect size to be detected (standardized or unstandardized), alpha, power, and from where values were derived. Prevalence and completeness will be compared among study designs, clinical populations, and with regard to journal reporting requirements. Results/Anticipated Results: At the pilot review stage, 17 of 25 included studies had any kind of sample size justification, and only 3 studies had enough information to reproduce their sample size calculations. Retrospective studies included a sample size justification more frequently (81.8% vs. 57.1%), but prospective studies had more complete sample size justifications, when present. We hypothesize that sample size calculations will be more complete in reports of clinical trials and prospective cohort studies, compared to retrospective and cross-sectional designs. Based on our previous research, we do not expect that journal reporting requirements will affect completeness of sample size justifications. Discussion/Significance of Impact: Translational decision-making is informed in part by the robustness of current research. Transparency of sample size considerations in publications can contribute to the formation of less biased opinions of translational readiness and, subsequently, more efficient and effective translation.

Objectives/Goals: Endometrial cancer is one of the few cancers that has both a rising incidence and mortality rate. Molecular classification is becoming more important for the management of endometrial cancer but the ability to translate this into clinical practice remains constrained. Our goal is to use AI to predict the molecular subtype from histopathology slides. Methods/Study Population: We utilized the open source endometrial cancer datasets from The Cancer Genome Atlas (TCGA) (N = 387) and Cancer Proteomics Transcriptomic Tumor Analysis Consortium (CPTAC) (N = 135) to develop and train a vision transformer AI model. We used a proprietary cohort of patients (N = 548) for external validation. Whole slide images (WSI) and molecular subtype data were collected. Subtypes include POLE ultramutated (POLE), microsatellite instability (MSI-H), copy-number low (CNV-L), and copy-number high (CNV-H). WSI were preprocessed, and features were extracted. Modified STAMP protocol was used in training, utilizing a pretrained foundation transformer model (Virchow2). Cross-validation of the TCGA was used for initial training, followed by testing on the CPTAC dataset and validation on our proprietary cohort. Results/Anticipated Results: Fivefold cross-validation of the TCGA database (60% training, 20% testing, and 20% validation) developed a best overall model with a mean AUC of 0.74 (POLE 0.78, MSI-H 0.76, CNV-H 0.86, CNV-L 0.77). Overall precision 0.58, recall 0.55. CNV-H was the subtype with the most accurate prediction. CPTAC holdout testing revealed moderately high AUC (POLE 0.63, MSI-H 0.62, CNV-H 0.98, and CNV-L 0.76). Overall precision 0.54 and recall 0.58. Again, CNV-H was the most accurate prediction. Validation on our proprietary cohort revealed a drop in performance with overall mixed results by AUC (POLE 0.50, MSI-H 0.69, CNV-H 0.78, and CNV-L 0.61). Overall precision 0.57, recall 0.45. Again, CNV-H with the most accurate prediction but F1 score dropped from 0.77 in the CPTAC to 0.47 on validation. POLE was the least accurate prediction subtype. Discussion/Significance of Impact: The CNV-H subtype demonstrated robust performance, suggesting the model effectively captures the features associated with this subtype. CNV-L had moderate performance. MSI-H and POLE were notably lower. WSI-based AI models show translational potential for subtype prediction in the management of endometrial cancer but more work is necessary.