Objectives/Goals: This study sought to gather older adult feedback on UCHealth’s artificial intelligence (AI) based chatbot, Livi, to ensure it is accessible and easy to navigate for end users to access fall prevention resources near their homes after an emergency department (ED) visit. Methods/Study Population: UCHealth’s electronic health record and ED operations team implemented an automated process to provide high fall-risk patients access to Livi via a QR code in their after-visit summary. Patients can then access evidence-based free or low-cost fall prevention resources based on their location. TO gather older adult feedback, rapid iterative testing was conducted at 3 community events (a religious center, assisted living facility, and academic medical campus). Research team members introduced Livi using an iPad and invited participants to explore the tool. End user feedback was gathered through notes taken on one-on-one guided conversation emphasizing first impressions and suggestions regarding Livi. Results/Anticipated Results: Suggestions from 93 community members included increasing font size and the addition of languages. Further resource suggestions included the following: increased locations, home modifications, and self-fall risk assessment. Based on these recommendations, our team increased font size, implemented the ability to switch from English to Spanish, added additional resources for other Colorado regions, added the ability to self-screen for fall risk using the National Council on Aging’s 13-question Screener, and fall prevention tips. Discussion/Significance of Impact: Many older adults do not follow up with primary care after a fall, increasing risk for subsequent falls. While Livi offers a pragmatic solution to this, ensuring end users can navigate it is key, so gathering feedback was a critical step before assessing Livi’s impact via randomized trial.

Objectives/Goals: To develop and validate a Random Survival Forest model predicting individualized tactile sensory recovery after DIEP flap breast reconstruction, enabling personalized postoperative counseling and future clinical decision-support integration. Methods/Study Population: Neurotized DIEP flap reconstructions (2019-2025) with pressure-specified sensory device testing were analyzed for time to ≥ 50% tactile sensory recovery. A five-variable Random Survival Forest (RSF) (dual vs. single coaptation, BMI, age, operative time, mastectomy weight) was trained on an imputed dataset. Discrimination (C-index; 1 = perfect discrimination, 0.5 = random chance), 12-month accuracy (Brier score; 0 = perfect forecast, 1 = completely inaccurate forecast), and calibration (predicted vs observed recovery quartiles) were assessed. Representative cases illustrate patient-specific recovery curves. Results/Anticipated Results: Of 110 breasts, 60 achieved ≥ 50% recovery. Mean follow-up was 17.1 ± 1.7 months (median 12.8, 95% CI 9.7-19.7). The RSF achieved C-index 0.69. The mean predicted recovery increased from 32.3% at 6.13 months to 49.5% at 11.8 months, 56.2% at 17.7 months, and 60.8% at 24.1 months. Calibration at 12 months by quartiles of predicted recovery showed observed recovery 0% (Q1), 48.8% (Q2), 80.8% (Q3), and 100% (Q4). The corresponding mean predicted probabilities were 17.2%, 43.1%, 62.3%, and 77.0%, respectively. The RSF model demonstrated superior predictive accuracy (Brier = 0.099) compared with a Kaplan-Meier baseline (Brier = 0.247). The low-recovery case had predicted recovery 6.2% at 12 months. The median case tracked the cohort mean: 52.4%. The high-recovery case achieved 81.8% at 12 months. Discussion/Significance of Impact: A five-variable RSF provides individualized recovery trajectories with moderate discrimination and good internal calibration. The tool quantifies time-dependent probabilities and supports the development of a perioperative counseling tool to predict expected tactile recovery after neurotized DIEP flap breast reconstruction.

Objectives/Goals: The primary objective of this research is to examine current implementations of Artificial Intelligence (AI) models in clinical trials, focusing on advantages, limitations, and ethical considerations associated with their application in pediatric populations. Methods/Study Population: A comprehensive literature search was conducted using PubMed and Google Scholar databases. The initial search used the key terms “artificial intelligence” and “pediatric.” The results were refined to include publications from 2023 to 2025. The keyword “imaging” was added, focusing on studies exploring AI-based diagnostic tools. Articles were included if they had at least one of the following: (1) the need for pediatric-specific databases, (2) diagnostic accuracy within pediatric populations, or (3) ethical considerations in AI-driven pediatric research. Data were retrieved from ClinicalTrials.gov, where “artificial intelligence” was specified. Eligibility criteria were limited to pediatric participants and restricted to studies conducted in the USA to ensure regulatory consistency. Results/Anticipated Results: An analysis of trials from ClinicalTrials.gov further highlighted the underrepresentation of pediatric subjects in AI-related clinical research, emphasizing a critical gap in age-appropriate AI model development and validation. AI models demonstrate great potential for improving diagnostic accuracy, but effectiveness remains limited by lack of pediatric-specific training data. In pediatric chest imaging, AI algorithms achieved diagnostic performance comparable to adult populations in detecting bacterial pneumonia (Morcos et al., 2023). Conversely, a large-scale review of public medical imaging datasets revealed an increase in false-positive rates among younger patients, reflecting model performance disparities (Zamora et al., 2024). Discussion/Significance of Impact: Implementing AI-driven models can accelerate data analysis and streamline trial design. The application of AI models in pediatric clinical trials can accelerate the timeline for treatment and reduce misdiagnosis. Addressing data gaps and ethical considerations about consent and algorithmic bias are crucial to improve pediatric health outcomes.

Objectives/Goals: Telehealth introduces opportunities to improve access to Alzheimer’s disease and related dementias (ADRD) diagnostic services. We aim to investigate the effect of the 2020 Centers for Medicare and Medicaid Services (CMS) telehealth expansion (where virtual cognitive assessments were covered) on county-level prevalence of ADRD diagnoses. Methods/Study Population: A county-level difference-in-difference (DID) design was employed to investigate the change in ADRD prevalence among US 65+ fee-for-service beneficiaries from pre-expansion (2016-2019) to post-expansion (2021-2022) by comparing counties with and without broadband. 2016-2022 county-level ADRD prevalence estimates were defined by Chronic Conditions Data Warehouse methodology from the CMS Mapping Medicare Disparities Tool. Broadband presence was defined as counties with ≥1 high-speed internet provider and average download/upload speeds of 25/3 megabits-per-second. The parallel trends assumption was assessed using graphical and model-based approaches. Negative binomial regression models estimated the average effect of the CMS expansion on ADRD prevalence among counties with broadband. Results/Anticipated Results: Average county-level ADRD prevalence was 11.06% across the pre-expansion period and 7.15% post-expansion. Broadband was present in 70.35% of counties pre-expansion and 91.96% of counties post-expansion. Differences in ADRD prevalence by broadband were constant across the pre-expansion period. ADRD prevalence was 2.48% higher in counties with broadband versus counties without broadband post-expansion compared to pre-expansion (95% confidence interval (CI): 1.01, 1.04). Discussion/Significance of Impact: Improvements in ADRD detection may have occurred in counties with broadband following the CMS telehealth expansion. However, the effect is dwarfed by the substantial reduction in ADRD prevalence from pre- to post-expansion. This reduction is likely a consequence of the COVID-19 pandemic, which may have decreased overall diagnostic opportunities.

Objectives/Goals: Efficacy-and-Effectiveness Too (EE2) randomized clinical trials pair a controlled efficacy cohort with a pragmatic effectiveness cohort. We will deliver a Bayesian EE2 framework with interim go/no-go rules and adaptive cross-cohort borrowing for time-to-event endpoints. Methods/Study Population: We formalize three approaches: 1) simultaneous: both cohorts start together, and interim looks apply predictive success probability (PSP) to enable early efficacy or futility stopping within each cohort; 2) staggered: the trial begins with the efficacy cohort and, at 50% information, initiates the effectiveness cohort only if the PSP under a retained-effect assumption (e.g., ≥70% of the efficacy log-HR retained) exceeds a prespecified threshold; 3) sequential: the efficacy trial is completed first, and the effectiveness trial is designed using the efficacy posteriors. Across approaches, the Bayesian method relies on piecewise-exponential modeling with Gamma-Poisson conjugacy, Negative-Binomial predictive counts, and power or commensurate priors with robust discounting. Results/Anticipated Results: Operating characteristics (type I error, power, bias/coverage, borrowing Effective Sample Size) will be evaluated through simulation studies across heterogeneity scenarios and prior-data conflict. We will re-analyze the RUBY and NRG-GY018 endometrial trials (endpoints: Progression-Free Survival and Overall Survival) as EE2 case studies (efficacy: mismatch repair-deficient tumors; effectiveness: mismatch repair-proficient tumors) using dynamic borrowing and the appropriate interim logic to demonstrate feasibility, robustness, and gains in precision. We anticipate improved precision for each cohort and for the combined effect and stable decisions under partial retention. Discussion/Significance of Impact: This work provides the first end-to-end Bayesian EE2 toolkit spanning simultaneous, staggered, and sequential implementations, with interim rules, principled borrowing, and software, to accelerate the generation of generalizable evidence while safeguarding against prior-data conflict, advancing efficient, patient-centered translation.

Objectives/Goals: Adolescent suicide is a major and growing public health concern, as suicide-related hospital visits continue to rise. Additionally, brain regions implicated in suicide risk are still undergoing change during adolescence. Here, we explore the longitudinal impact of suicide risk factors on brain functional connectivity during adolescence. Methods/Study Population: Data from the Adolescent Brain and Cognitive Development (ABCD) Study were used for this analysis. The ABCD Study is an ongoing, multi-site, longitudinal study that follows kids starting at 9 years old until they’re 18 years old. The study sample is meant to be representative of the current US population, based on various demographic criteria obtained from the US census. For this study, baseline and Year 2 functional MRI imaging data and parent and youth reports of depression, non-suicidal self-injury (NSSI), and suicidal thoughts and behaviors (STB) from the ABCD Study, were used for this analysis. Clinical and imaging data were added into a statistical model (linear mixed-effects model) to describe how the relationship between suicide risk and brain development changes over time. Results/Anticipated Results: A total of 9653 subjects (51% Female), between the ages of 8.9 – 13.8 years, across two timepoints: Baseline (N=6493) and Year 2 (N=3,160), were included in the analysis. Of this sample, 861 (8.9%) endorsed depression, 1428 (14.8%) NSSI, 2146 (22.2%) STB, and 3012 (31.2%) any of the three suicide risk factors at any timepoint. Results showed a significant interaction between the association of network connectivity and STB group status with age in the approach (B = -15.0, 95%CI [-26.4, -3.8]), avoidance (B = -8.5, 95%CI [-16.3, -0.9]), regulation (B = -14.4, 95%CI [-26.2, -3.1]), approach-avoidance (B = -14.4, 95%CI [-28.3, -0.5]), and approach-regulation (B = -15.6, 95%CI [-28.8, -2.7]) network. Discussion/Significance of Impact: Findings suggest, in early adolescence, presence of STBs is associated with changes in communication in regions involved in reward-(approach), emotion/threat-processing (avoidance), and their cognitive regulation (regulation). The causal relationship is unclear, but it’s an important step to understanding the neural mechanisms of suicide.

Objectives/Goals: Misinterpreting hazard ratio (HR) as absolute risk reduction is common in randomized trials (RCTs) with time-to-event endpoints, inflating benefit. We quantify this by describing risk ratio (RR) estimators for survival data and compare HRs with milestone and time-averaged RRs across a large collection of cancer RCTs. Methods/Study Population: We conducted a meta-epidemiological study in a convenience sample of more than 650 cancer RCTs (2002–2024), excluding trials without reported benefit, those stopped early, or non-inferiority designs. Pseudo-individual patient data were reconstructed from survival curves for overall survival and other event-free endpoints (such as progression-free survival). From these, we calculated Cox HRs and milestone-based RRs on common time supports. We also calculated time-constant RRs and weighted-averages of time-varying RRs. Primary contrasts were inverse-variance pooled HR/RR ratios for each RR definition. HR/RR < 1 indicates larger effects with HR as compared to RR. Results/Anticipated Results: In a preliminary subset (n=120 trials), the pooled HR/RR ratio was 0.80 (95% confidence interval, 0.76 to 0.82): interpreting the HR as a RR would overstate benefit by 20%. Although all included trials reported statistically significant HR < 1, only 73% had RR < 1 and statistically significant: over one quarter failed to show benefit on the absolute risk scale. Results were consistent when using time-constant and weighted-average RRs. We anticipate comparable findings in the full sample. Discussion/Significance of Impact: This study quantifies the inflation that arises when HRs are read as RRs. Reporting RR estimators for time-to-endpoints alongside HRs would improve communication of trial effects. Our findings also have design implications: to detect absolute risk reductions, RCTs would often need larger N or longer follow-up.

Objectives/Goals: Pediatric ocular hypertension (OHTN) carries a variable risk of glaucoma progression, yet its progression to true glaucoma is not well-defined. This study characterizes the clinical course of a cohort of pediatric eyes with OHTN and identifies predictors to glaucoma conversion. Methods/Study Population: A retrospective review of 119 eyes from 81 pediatric glaucoma suspects (IOP >21 mmHg on ≥2 visits) between 2005–2016. Conversion to glaucoma was defined by the Childhood Glaucoma Research Network criteria (progressive optic nerve cupping, visual field loss, or other structural changes associated with elevated IOP). Demographics, comorbidities, and tonometry methods were analyzed. Logistic regression identified independent risk factors for glaucoma conversion. Thus far, analyses include data from the 2005–2016 cohort, with additional data from the 2017–2023 patient cohort under collection and expected to be ready by the conference date. Results/Anticipated Results: Of 119eyes (age 9.4±4.7years; baseline IOP27.7±5.7mmHg), 47(39.5%) converted to glaucoma over average 1.9years.Among 72 non-converters, 23(31.9%) normalized without treatment, 17(23.6%) with treatment, 17(23.6%)remained elevated untreated, and 15(20.8%) with treatment. Conversion was most frequent with baseline IOP 24–28mmHg(16.0%)and less with <24mmHg(8.3%). Absence of ocular (11.8%vs50.6%) and systemic risk factors (36.0%vs48.5%) reduced conversion, lowering treatment need and improving normalization. On multivariable analysis, younger age (OR0.84/year, p=0.002), ocular risk factors (OR4.95,p=0.01), and time to therapy initiation (OR0.74/year, p<0.001) predicted conversion. Discussion/Significance of Impact: This study establishes baseline age and ocular risk factors as strong predictors of glaucoma conversion in pediatric ocular hypertensives. These findings are critical for clinicians, directly guiding an evidence-based approach to patient risk stratification, surveillance frequency, and treatment initiation.

Objectives/Goals: Identify host ecology factors that lead to the emergence of highly pathogenic avian influenza (HPAI) variants shown to be more fit than others and that become variants of concern to agriculture, wildlife, and humans. Goals include targeted surveillance for these variants for enhanced biosecurity measures in agriculture and pandemic preparedness. Methods/Study Population: The study dataset of 721 HPAI-positive cases in wild birds in New England since 2022 was collected through a robust sampling effort by Tufts’ Runstadler Laboratory together with a large network of wildlife rescue and rehabilitation partners. We will fit mixed-effects models to measure the association of variant fitness as a fixed effect with the odds of infection in species of either of the two bird orders most associated with HPAI – gulls and shorebirds or ducks and geese. Variant will be fit as a random effect, and covariates will include ecological factors. Fitness will be a leveled variable based on prevalence, geographic spread and host range. Using centroid spatial statistics, we will determine whether these variants traveled geographically distinct transmission routes, indicating distinct host ecologies. Results/Anticipated Results: We anticipate that birds of the order Charadriiformes (seagulls and shorebirds) will be more associated than Anseriformes (ducks, geese) with HPAI variants that were not transmitted beyond the region and that the reverse will be true with variants that did achieve prevalence over a wide geographic range and range of host species, including agricultural species. We also anticipate that there are distinct transmission routes by variant that could better illuminate host ecology dynamics in this region that contribute to variant fitness. Discussion/Significance of Impact: The current HPAI virus outbreak is perpetuated by evolution to new variants through co-infections in wild birds with low pathogenic avian influenza viruses they carry. This research could lead to study of the virulence to different wild bird host species of low pathogenic avian influenza subtypes that contributed genetic material to an HPAI variant.

Objectives/Goals: To develop a novel meta-analysis model that estimates pooled risk ratios (RR) at prespecified milestones, accounts for unequal follow-up across trials, and leverages between-time correlation, thereby providing clinically interpretable estimates under potential non-proportional hazards (PH). Methods/Study Population: Our model combines study-specific RRs – the ratios of cumulative event probabilities – from Kaplan-Meier curves at prespecified times (12, 24, 36 months, etc.). Using the delta method, we derive within-trial variances for log-RRs and cross-time covariances to reflect correlation among milestones. These study-level estimates and variance-covariance matrices enter a multivariate random effects model to obtain pooled RRs. We illustrate this method with a meta-analysis of progression-free survival in 7 randomized clinical trials of first-line therapy immunotherapy combinations in metastatic renal cell carcinoma. Results/Anticipated Results: Follow-up for PFS across the 7 trials was heterogeneous: all 7 trials contribute at 12 months, 6 at 24 months, 5 at 36 months, 4 at 48 months, and only 2 contributing at 54 and 60 months. This heterogeneity motivates a multivariate approach that borrows strength across times. PH diagnostics indicate deviations from PH for PFS in 3 trials, supporting the need for pooled effects at milestones rather than a single summary measure. We will report pooled RRs at 12, 24, 36, 48, 54, and 60 months. We expect the multivariate model to improve precision at shared milestones while honestly reflecting increasing uncertainty at sparse later times. Discussion/Significance of Impact: When follow-up differs across trials and PH is questionable, a multivariate RR meta-analysis preserves interpretability and efficiently uses all available milestones without forcing a single-number summary. This approach clarifies when benefits accrue and provide clinically interpretable results.

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: Discharges before medically advised (BMA) – also known as “against medical advice” – after an asthma exacerbation are associated with adverse outcomes, including recurrent hospitalization, but the reasons for this are unclear. We sought to evaluate whether gaps in prescribing maintenance inhalers were associated with recurrent hospitalization. Methods/Study Population: All asthma exacerbations, defined by ICD-10 codes, among adults requiring an emergency department (ED) visit or hospitalization at any of 5 hospitals in our health system were classified as BMA or non-BMA (i.e., planned) discharges using EHR data. We evaluated whether an inhaled corticosteroid and long-acting beta-agonist (ICS/LABA) inhaler was prescribed on discharge, and whether they had a recurrent exacerbation within 30 days. We used logistic regression models adjusted for age, sex, exacerbation history, medical center, encounter type (ED or admission), BiPAP use, insurance, prior ICS/LABA prescription to evaluate risk of 30-day re-exacerbation by ICS/LABA prescription, BMA discharge, and the interaction between those variables. Results/Anticipated Results: This cohort included 13,064 exacerbations, and 330 (2.5%) resulted in BMA discharge. Compared to non-BMA discharges, those discharging BMA were younger (40 vs 43 years) and less often female (48% vs 64%). Those discharging BMA were less likely to receive an ICS/LABA prescription (16% vs 23%, p=0.01) and more likely to experience 30-day re-exacerbation (12% vs 7%, p=0.001). In adjusted analyses, BMA discharge increased the risk of 30-day re-exacerbation (OR 1.79, 95% CI: 1.22-2.64) and ICS/LABA prescription was protective (OR 0.79, 95% CI: 0.65-0.96). There was a significant interaction (OR for interaction: 0.11, 95% CI 0.01-0.85), indicating a stronger protective association of ICS/LABA among those discharging BMA. Discussion/Significance of Impact: Prescribing an ICS/LABA at discharge protects against recurrent severe asthma exacerbations within 30 days. This association is strongest among those discharging BMA, highlighting this susceptible population as requiring further attention to address gaps in care.

Objectives/Goals: Findings from cohort studies report a 1-year major adverse cardiac event (MACE) rate of 15% after vascular surgery. However, the real-world evidence (RWE) of the timing, incidence, and profile of these events is limited. We hypothesize that the MACE rate from RWE data will exceed current estimates. Methods/Study Population: Patients undergoing elective, intermediate- or high-risk vascular surgery at University of Maryland Medical System (1/1/2016—9/30/2025) were analyzed retrospectively. Data on six MACE outcomes (all-cause mortality, myocardial infarction, coronary revascularization, heart failure decompensation, cardiogenic shock, nonfatal cardiac arrest) were extracted from the Electronic Health Record utilizing algorithms incorporating ICD-10 codes, Current Procedural Terminology (CPT) codes, and clinical variables. We calculated the cumulative postoperative MACE incidence at 7-days, 30-days and 1-year following surgery. Results/Anticipated Results: We identified 9,490 patients of whom N=6,180 (65%) were male, N=6,327 (67%) were white, and N=2,755 (29%) were black or African American. We will describe baseline characteristics, comorbidities, pre-operative radiographic results and laboratory values for the study cohort. The primary endpoint is cumulative MACE incidence at 30-days. Secondary endpoints include composite MACE incidence at 7-days and 1-year, as well as outcomes stratified by individual MACE parameters. Discussion/Significance of Impact: This retrospective study aims to provide a detailed characterization of MACE following vascular surgery. The derived data are anticipated to inform pre-operative risk stratification for real-world scenarios and in doing so identify opportunities for preventative interventions targeting MACE.

Objectives/Goals: Develop a reliable methodology to deliver and study asphalt emission exposure on lung physiology, enabling the assessment of acute volatile organic compound (VOC) effects with minimal confounding, and test filtration techniques for efficacy. Methods/Study Population: Sixteen healthy adults (18-50 years) visited the Mayo Clinic cardiopulmonary research lab in Scottsdale, Arizona. Subjects wore a mask fitted with a one-way breathing valve connected to a mixing chamber where they would inhale the VOCs that come from a cocktail of chemical compounds captured from heated asphalt. These VOCs were administered by study staff every 5 minutes for a total of 60 minutes of exposure. Pulmonary measures recorded before and after exposure included respiratory oscillometry, exhaled hydrogen peroxide and nitric oxide, diffusion capacity of the lungs for carbon monoxide and nitric oxide, lung ultrasound, basic spirometry, and transcranial Doppler ultrasound. Results/Anticipated Results: The VOCs delivered replicate urban environmental exposure on hot days, consistent with literature linking high VOC exposure to pulmonary disease and cancer. Preliminary findings show acute changes in alveolar-membrane conductance (DM; mean Δ=53.1 mL/min/mmHg) when unfiltered VOCs were administered. This response was accompanied by increased function gas exchange units (DM/Vc; mean Δ=1.027). These early findings confirm successful implementation of the exposure method and suggest reproducible physiologic responses to acute VOC exposure. Completion of this study is expected to reveal additional markers of pulmonary inflammation and validate a controlled, scalable platform for testing VOC exposure in the laboratory setting. Discussion/Significance of Impact: These methods are the first of their kind to provide a means to study the acute effects of exposure to asphalt in humans in a controlled, laboratory environment. This offers great significance in understanding the environmental exposures that are affecting the health of those that are exposed to asphalt daily.

Objectives/Goals: The objective of this study was to evaluate whether exposure to air pollution (PM 2.5) and neighborhood deprivation are associated with prostate cancer risk among men in Baltimore and to determine if social and environmental factors jointly influence disparities in prostate cancer occurrence among men. Methods/Study Population: This case–control study was conducted in the Greater Baltimore area between January 2005 and January 2016. Participants included 617 men with prostate cancer and 852 controls without prostate cancer of African and European descent. Individual data on demographics, smoking, BMI, income, and education were collected through chart review. Residential addresses were linked to neighborhood deprivation index (NDI) and average fine particulate matter (PM₂.₅) levels for 2010 using geospatial data. Logistic regression models were used to estimate associations between PM₂.₅, NDI, and odds of prostate cancer, adjusting for race, smoking, income, education, and BMI. All analyses were conducted using complete-case data. Results/Anticipated Results: In complete-case logistic regression of prostate cancer case status (n = 1,856), unadjusted PM₂.₅ (per 1 µg/m³) was positively associated with odds of prostate cancer (unadjusted OR for developing prostate cancer per 1 µg/m³ = 1.35; p = 0.014). After multivariable adjustment for neighborhood deprivation index (NDI), race, smoking, income, education, and BMI, the association between PM₂.₅ and case status was attenuated and not statistically significant (adjusted OR per 1 µg/m³ = 0.78; 95% CI 0.59–1.04; p = 0.088). By contrast, NDI was associated with higher odds of developing prostate cancer in adjusted models: adjusted OR per 1-unit increase in NDI was 1.15 (95% CI 1.09–1.21; p < 0.001). Using a standardized effect, the adjusted OR per 1 SD increase in NDI was 1.41 (95% CI 1.23–1.61). Discussion/Significance of Impact: Neighborhood deprivation was significantly associated with higher odds of prostate cancer, independent of race, smoking, income, education, and BMI. PM₂.₅ showed no independent association after adjustment, suggesting socioeconomic context may underlie observed disparities in prostate cancer incidence.

Objectives/Goals: To quantify the association between proximity to harm-reduction vending machines and recurrent nonfatal overdose using recurrent-event survival models, estimate effects on time to reoverdose and hazard, and identify modifiable predictors to guide machine sitting. Methods/Study Population: Retrospective cohort of Milwaukee County nonfatal overdoses, Jan 2018 to Dec 2023 (28,108 events; 20,300 people). Records were geocoded, deduplicated, linked within person, and tagged as single or recurrent. Exposure: residence or event within a 30 min walk of a harm-reduction vending machine. Recurrence summarized with Kaplan-Meier curves and mean cumulative function. An interrupted time series (ITS) assessed pre- vs post-HRVM expansion. For inference, we compared Andersen-Gill, Prentice-Williams-Peterson, and Cox ML models, selecting AG gap time. Covariates: age, sex, race, jurisdiction, location type, disposition, proximity. Assumptions checked; hazards reported with 95% CIs. Results/Anticipated Results: 2018 to 2023: 28,108 nonfatal overdoses among 20,300 people; 3,803 had repeats (11,611 events). Inter-event times shortened with each recurrence. Kaplan–Meier for first to second overdose showed small, consistent separation favoring those within 30 min of HRVMs; mean cumulative functions rose more slowly near HRVMs. The selected Andersen–Gill gap-time model found no meaningful short-term effect of proximity (aHR ≈ 1.03, 95% CI 1.00–1.06). Younger age and public or commercial locations predicted faster recurrence. County ITS suggested stabilization after HRVM expansion without a clear early reduction. Discussion/Significance of Impact: Early HRVM rollout yields small reductions in cumulative recurrence without a meaningful short-term hazard change. Results support MOUD linkage and mobile outreach targeting younger people and public settings. The recurrent-event and ITS framework is generalizable for sitting and monitoring.

Objectives/Goals: Mass incarceration, i.e., extremely high rates of incarceration concentrated in impoverished racially segregated communities, is associated with poor neighborhood health, but it is unclear if this is due solely to formerly incarcerated individuals. We examine these population health effects through neighborhood premature mortality rates. Methods/Study Population: We calculated census tract-level overall, gender-, and race-specific age-adjusted premature mortality rates using mortality data (2010-2014) from the New York City Department of Health. We excluded tracts with subgroup population <800. Exposure was the NY State imprisonment rate (2010), modeled as quintiles. As covariates, we included % non-Hispanic Black; poverty, education, and violent crime rates; and population density. We used GLM regression models with the census tract as the unit of analysis. To test if spatial clustering of incarceration (i.e., high-incarceration census tracts surrounded by high-incarceration census tracts) was associated with premature mortality rate independent of covariates and tract incarceration rate, we used LISA cluster values and proximity to high-high clusters. Results/Anticipated Results: Across 1985 tracts, incarceration rate ranged from a median of 19 (quintile 1) to 698 (quintile 5) per 100,000 people. In unadjusted models, neighborhoods in Q5 of incarceration rate had 2.4x higher rate ratios of premature mortality versus Q1. In fully adjusted models, Q5 tracts had 62% higher rate ratios (aOR 1.62, 95% CI 1.50-1.75; P<0.001), sex-specific findings were similar for males and females, Black and Hispanic (aOR 1.36; 95% CI 1.04-1.78 and aOR 1.49, 95% CI 1.24-1.79, specifically) rate ratios were both P<0.001 but Asian and White were NS. Being in a high-high cluster was significantly associated with premature mortality independent of covariates and tract incarceration rate (aOR 1.13, 95% CI 1.06-1.20), whereas low-low clusters were protective (aOR 0.90, 95% CI 0.85-0.94), both P<0.001. Discussion/Significance of Impact: Premature mortality rates are substantially higher in high-incarceration neighborhoods even accounting for confounders. Sex-specific findings suggest spillover to never-incarcerated people, and race-specific findings suggest concentration in social networks of the incarcerated. Spatial analyses suggest true neighborhood-level effects.

Objectives/Goals: Quantify environmental persistence and airborne stability of avian (aMPV) and human metapneumovirus (hMPV) and evaluate far-UVC light (at 222 nm) as a safe, non-chemical disinfection method to reduce viral transmission in agricultural and healthcare environments. Methods/Study Population: Subtypes A and B of aMPV and subtype B of hMPV isolates will be propagated in Vero and LLC-MK2 cells, respectively. Viral persistence will be quantified on fomites under varying temperature and humidity. Aerosol stability will be assessed using an environmental chamber and an atomizer system. Once baseline survival is established, samples and aerosols will be exposed to different far-UVC doses, intensities, and durations. The endpoints will be determined by observing cytopathic effects (CPE), virus titers will be calculated by the Karber method, and titers will be expressed as TCID50. Results/Anticipated Results: We anticipate quantifying surface and aerosol stability profiles of aMPV and hMPV across several porous and non-porous materials (fomites) and environmental conditions relevant to poultry and clinical settings. Far-UVC exposure is predicted to achieve rapid viral inactivation on non-porous surfaces and in aerosols without measurable cytotoxicity or material degradation. The findings will establish disinfection thresholds and demonstrate the practicality of far-UVC integration into real-world agricultural and healthcare biosecurity systems. Discussion/Significance of Impact: This work advances One Health biosecurity by establishing safe far-UVC disinfection protocols to control the spread of both aMPV and hMPV. Findings will inform infection control policies and reduce economic and health burdens in poultry operations and vulnerable human populations.

Objectives/Goals: In peri- and postmenopausal women, to determine 1) whether vasomotor symptoms (VMS) reflect underlying vascular and skeletal muscle dysfunction as well as cardiorespiratory fitness (CRF) and 2) to assess the impact of hormone replacement therapy (HRT) on VMS, vascular and muscular function, and CRF. Methods/Study Population: Peri- and postmenopausal women with 1) no/mild, 2) moderate, or 3) severe VMS will be recruited. Muscle and vascular function as well as CRF will be assessed at baseline and after 3 months in women who initiate VMS-specific therapy (HRT vs. SSRIs). Muscle function will be assessed as quadriceps strength (MVC), size (ultrasound), and contraction kinetics (nerve stimulation). Vascular function will be assessed as brachial flow-mediated dilation and carotid artery measures including intima-media thickness. CRF will be assessed during a graded cardiopulmonary exercise test. VMS will be tracked via ambulatory skin temperature, blood pressure, and heart rate (via wearable device(s)) and patient symptomology diaries completed during the 1st, 6th, and 12th week after treatment initiation. Results/Anticipated Results: We anticipate that 1) increasing VMS severity will be associated smaller muscle size and impaired function, worse vascular function, and lower CRF after correcting for independent variables (e.g., age, time in peri/menopause, BMI, and ethnicity); 2) HRT will result in great improvements in muscle and vascular function and CRF, as well as greater alleviation of VMS, compared to SSRIs initiation. Discussion/Significance of Impact: This research will elucidate potential physiological system correlates and dysfunction that occur during VMS events. This insight into the physiological underpinnings of VMS will inform optimal management strategies that can improve quality of life and cardiovascular health in menopausal women.

Objectives/Goals: Black women are adversely affected by HDP. Allostatic load is linked to poor pregnancy outcomes in Black women, but studies on its relation to HDP are limited and inconsistent, especially regarding racial disparities. The review aims to examine existing research on the association between allostatic load and HDP. Methods/Study Population: For this SCOPING review, a comprehensive search will be conducted of peer-reviewed literature in PubMed, Medline, Ovid Embase, Cochrane Library, and Google Scholar from database inception to October 1st, 2025. Relevant search terms will be used to identify studies that measure the exposure of allostatic load, a marker of chronic stress and the outcomes of hypertensive disorders of pregnancy, including preeclampsia, hypertension, and high blood pressure. Studies that discuss chronic stress as an exposure will also be included as a proxy measure of allostatic load. Inclusion criteria include a population of pregnant women and the availability of the study in English. This review will be conducted according to PRISMA guidelines. Results/Anticipated Results: This project is ongoing. Findings from this review will highlight the current landscape of literature exploring the association between allostatic load and HDP. Results will be organized into studies on allostatic load and HDP, chronic stress and HDP, and studies exploring racial differences in this association. Based on the findings, we hypothesize a correlation between allostatic load and HDP throughout the literature, with a particularly strong association observed among Black women. Discussion/Significance of Impact: The results of this review will offer insights into the relationship between allostatic load and HDP. This study will help establish a foundation for future research exploring this association and make the case for stress-reducing interventions as strategies to decrease racial disparities in maternal morbidity related to stress and HDP.