Objectives/Goals: Our goal is to enhance communication and documentation in collaborative biostatistics by refining data management and metadata processes. We aim to capture critical data collection and generation information, improve transparency and reproducibility, and foster stronger researcher partnerships for more effective collaborations. Methods/Study Population: Traditional statistical analysis plans (SAP) often miss essential contextual knowledge from collaborators, leading to gaps that hinder reproducibility and limit future data use. Biostatistics teams at the University of Kentucky have updated their strategies to better capture important details about data origins and collection processes. By focusing on clear, comprehensive documentation early in the research process, we aim to preserve foundational data insights and improve collaboration efficiency. Our Biostatistics, Epidemiology, and Research Design (BERD) team has established best practices for addressing data management structures with collaborators across medical and healthcare fields – covering all project stages, from initial data collection to metadata creation and dataset finalization. Results/Anticipated Results: We will detail the processes used to improve data management structures and the observed results of these processes. For example, initiating deeper discussions about data origins and collection processes as early as possible in the collaboration has resulted in a more comprehensive project narrative that lays the foundation for effective collaboration. By engaging with project leaders early in the process, we can confirm that critical details about how data were collected and processed are documented, improving both the transparency and reproducibility of research findings. Streamlining the processes of capturing this information makes it more accessible and useful for those with limited statistical backgrounds, which is particularly relevant for faculty and staff in BERD communities and Clinical and Translational Science Awards Programs. Discussion/Significance of Impact: Nuanced data documentation structures are crucial for transforming raw data into meaningful, reusable datasets. Our initiatives promote clear communication, enhanced efficiency, and streamlined workflows. Translational science researchers can benefit from improving data management and metadata to boost long-term collaborative success.

Objectives/Goals: 1) Determine the association between wildfire smoke-driven PM2.5 and risk of persistent respiratory symptoms and repeated asthma exacerbations after the acute wildfire period among adults with asthma. 2) Examine how measures to reduce personal exposure to wildfire smoke, including avoiding outdoor activities, modify this association. Methods/Study Population: This is a retrospective study of adults with asthma in WHAT-NOW, a cohort study of people living in Northern California during the 2018 Camp Fire. Daily smoke-driven PM2.5 was estimated for each participant based on their home address or evacuation location. We examined the association between mean PM2.5 exposure and the presence of respiratory symptoms at both the time of the survey (6–16 months post-wildfire) and at least one other post-wildfire time-period, as well as whether they had a medically attended respiratory illness (saw a doctor, visited the ER, or were hospitalized for a respiratory symptom). We examined the interaction of PM2.5 with spending time outdoors during the wildfires. Poisson regression models with robust standard errors were adjusted for age, sex, race, smoking, allergies, and education. Results/Anticipated Results: Among 337 adults with asthma in the WHAT-NOW cohort, one standard deviation higher smoke-driven PM2.5 was associated with higher risk of any persistent respiratory symptom (risk ratio (RR) 1.38, 95% CI 1.07 – 1.78) and having at least one medically attended respiratory illness (RR 1.33, 95% CI 1.07 – 1.65), but not significantly associated with repeated asthma exacerbations (RR 1.30, 95% CI 0.92 – 1.81). However, there was a significant interaction between PM2.5 and outdoor activities during the wildfire on the outcomes of any persistent respiratory symptoms (p = 0.041) and repeated asthma exacerbations (p = 0.028). The association between PM2.5 and repeated asthma exacerbations was greater among people who spent time outdoors (RR 3.36, 95% CI 1.47 – 10.23) than those who did not (RR 1.00, p = 0.99). Discussion/Significance of Impact: This study provides evidence that exposure to wildfire smoke increases respiratory morbidity among adults with asthma beyond the acute wildfire period. Additionally, it suggests that avoiding outdoor activities on smoky days can significantly decrease the risk of future repeated asthma exacerbations associated with smoke exposure.

Objectives/Goals: Using secure systems for sharing documents with external collaborators is essential for all researchers. These documents may include protected health information (PHI) or sensitive materials like protocols, study reports, DSMB reports, publications, presentations, abstracts, and statistical analysis plans (SAPs). Methods/Study Population: We surveyed the ACTS Biostatistics, Epidemiology, and Research Design Special Interest Group (BERD-SIG) to gather information about the systems they are currently using or have used in the past for document sharing with external collaborators. The survey focused on the security of these systems, particularly in relation to sharing documents containing PHI. In addition, the survey included questions about various system features of interest. These features included version control, simultaneous editing by multiple users, and access rights management, such as the ability to assign different permissions (e.g., read-only, write, and download) to different individuals. We also invited participants to provide feedback on any additional positive or negative aspects of the systems they use. Results/Anticipated Results: We received 28 completed survey responses. Respondents had an option for choosing more than one system. The top current systems reported were Microsoft Teams (OneDrive, SharePoint) (n = 16), Box (n = 11), Google Docs/Drive (n = 10), and Dropbox (n = 6). Among other systems listed individually were Filelocker, REDCap, Slack, Website, Significant Media Shuttle, and Zulip. Notably, 15 responses indicated the respondents were unsure if their system is secure for sharing documents containing PHI. Respondents also offered feedback on both the positive and negative aspects of these systems. For example, a key advantage of Box was its password-controlled access. However, its incompatibility with office tools and the challenges for external collaborators attempting to access the system were noted as drawbacks. Discussion/Significance of Impact: Utilizing secure institutional document-sharing systems and understanding their features significantly affects the effectiveness and security of collaborations among researchers, particularly with external partners. This knowledge is especially crucial when sharing documents containing sensitive patient and study data.

Objectives/Goals: Poor visual memory and perceptual organization task performance predicts cognitive decline and is sensitive to dementia severity. No genome-wide association study (GWAS) has assessed the genomic basis of cognitive visual-spatial phenotypes. We aimed to identify common genetic variants associated with visual memory and spatial organization. Methods/Study Population: We included dementia- and stroke-free participants aged 45 years or older from up to seven cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, who performed cognitive tasks assessing delayed visual memory (e.g., Benton Visual Retention Test (BVRT, n = 10,934) and visual reproductions (VR, n = 5,527)) or spatial organization (i.e., Hooper Visual Organization Test (HVOT, n = 5,024)). Each cohort used linear regression models to relate common genetic variants imputed to the 1000 Genomes panel to each cognitive phenotype, adjusting for age, sex, population stratification, and education. Summary statistics for the BVRT were meta-analyzed using METAL. Combined GWAS was used for a joint analysis of all traits. Results/Anticipated Results: We identified a genome-wide significant variant related to BVRT performance located near the TSHZ3 gene (rs10425277, p = 6.76×10–9). TSHZ3 is important for the development and function of cortical projecting neurons and may be implicated in Alzheimer’s disease progression by repressing CASP4 transcription. Multitrait analyses, including BVRT, VR, and HVOT, identified two additional variants of interest in SMYD3 gene (rs10802275, p = 5.58×10–7) and near ZFPM2 (rs2957459, p = 2.03×10–7), both of which are overexpressed in the brain and have important implications for neurodevelopment. SMYD3 may be directly involved in synaptic dysfunction and has been shown to be upregulated in the prefrontal cortex of Alzheimer’s disease patients. Discussion/Significance of Impact: Our findings suggest that variants related to visual memory and spatial organization are involved in neurodevelopmental and degenerative pathways. This GWAS adds to the growing body of GWAS literature on the genetic basis of cognitive function. Additional analyses are underway to replicate these findings and extend functional annotation.

Objectives/Goals: Longitudinal studies capture dynamic host–environment interactions crucial to microbiome research. Commonly used mixed-effects models can struggle with small clinical samples, like many endometrial cancer studies. We will compare them to simpler fixed-effects models, aiming to develop a new fixed-effects differential abundance alternative. Methods/Study Population: Starting with simulated data for linear models with a single treatment effect, we will incrementally increase complexity to reflect real-world microbiome data. To observe conditions of misspecification, simulated data of repeated measures will be generated using different distributions, while varying parameters and inter-class correlation. In each condition, linear fixed- and mixed-effects models will be fitted 1000 times to empirically determine p-value, type 1 error rate, and power. We will increase the verisimilitude of our approach by using endometrial cancer data from our lab as a real background, while adding simulated signals. This data will be used to assess extant differential abundance models against our novel fixed-effects model. Results/Anticipated Results: Our initial findings indicate that fixed-effects models maintain control over type 1 error rates in small samples, while mixed-effects models do not perform as reliably. We are now exploring the effects of confounders on type 1 error rates and power in linear models, while our next step will evaluate generalized linear models in a differential abundance context. We expect that the fixed-effects models will continue to be as reliable as mixed-effects models, while being less computationally complex. After establishing our theoretical basis, our novel model should perform comparably to mixed-effects models on pseudo-simulated endometrial cancer data and better at small sample sizes. We will finally apply our model to real endometrial cancer data to identify microbial markers of disease predisposition. Discussion/Significance of Impact: By characterizing and improving these statistical tools, we seek to increase the robustness and power of microbiome study results (especially at small sample sizes), ultimately supporting better-informed translational research decisions. This work underscores the importance of statistical methods in advancing microbiome research.

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

Objectives/Goals: Telehealth is a key solution to improving access to healthcare and disease detection, especially in rural areas. Telehealth access relies on the presence of broadband in an area, which has shifted with the growing importance of internet. We aim to assess the distribution of US county-level broadband availability from 2017 to 2020 overall and by rurality. Methods/Study Population: We employed an ecologic study design to examine the distributions of two measures of broadband availability across all US counties from 2017 to 2020. Broadband presence was defined as counties meeting the Federal Communications Commission (FCC) definition of broadband with at least one high-speed internet provider and an average download/upload speed of at least 25/3 megabits per second using 2017–2020 FCC Broadband Deployment Data. Broadband access, or county-year proportion of households with broadband, was defined using 2017–2020 data from the American Community Survey. We used log-binomial and linear regression models and a difference-in-difference analytical approach to estimate the difference in the change in broadband presence and access from 2017 to 2020 between rural and urban counties. Results/Anticipated Results: Overall, broadband presence increased across the study period, where 66.82% of counties had broadband present in 2017 versus 92.57% in 2020. A major jump occurred from 2018 to 2019, where 64.96% of counties had broadband present in 2018 compared to 91.09% in 2019. Broadband access also rose, where the average proportion of households with broadband was 69.43% in 2017 and 78.24% in 2020. The increase in both broadband presence and access from 2017 to 2020 was larger in rural counties compared to urban counties. Specifically, the increase in the probability of having broadband present from 2017 to 2020 was 30% higher in rural compared to urban counties (95% CI: 1.24, 1.38). The increase in the proportion of households with broadband was 1.21% higher from 2017 to 2020 in rural compared to urban counties (95% CI: 0.004, 0.021). Discussion/Significance of Impact: While broadband presence and access both increased from 2017 to 2020, the observed increases were larger in rural compared to urban counties. Improvements in broadband access in the US are continuously needed to increase the use of telehealth and, subsequently, lessen rural/urban disparities in healthcare access and disease detection.

Objectives/Goals: Approximately 250,000 anterior cruciate ligament (ACL) tears occur annually in the USA. Symptoms generally improve after ACL reconstruction (ACLR), but 20% of athletes do not return to sport. It is not clear how biomechanical function and mental health impact return to activity, so the purpose of this study is to evaluate their effect on return to activity following ACLR. Methods/Study Population: Patients age 18 years and older who have undergone primary ACLR at a single institution who are one year out from their initial procedure will be recruited by email. Patients will be excluded if they had a concomitant or subsequent ligamentous knee injury in the follow-up period since their index procedure. Additionally, patients will be excluded if they do not have access to a mobile phone with video recording capability. The primary outcome will be joint angle kinematics and postural balance metrics derived from patient recorded mobile-phone videos while performing several provocative exercises (sit-to-stand, Star Excursion Balance test). Patients will also be given surveys assessing knee symptoms, psychological readiness for return to sport, mental health, athletic history, and current return to sport level. Results/Anticipated Results: We predict that psychological readiness for return to sport following ACL injury and biomechanical postural stability will each be independently associated with return to sport timing following ACLR. Additionally, we anticipate that psychological readiness, as measured by higher ACL-Return to Sport Index scores, will be more strongly associated with return to sport compared to biomechanical movement quality (better gross postural control on skeletal modeling). In other words, higher psychological readiness for return to sport will have a stronger independent association with return to sport level compared to biomechanical movement quality measures. Discussion/Significance of Impact: This study also aims to define return to sport in terms of biomechanics and psychological readiness in an athletically heterogenous population. Additionally, we will test the feasibility of patient-led, remote, mobile, marker less motion capture for assessment of biomechanical function and distribution of patient-reported outcome measures.

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: Aim 1: Assess the correlation between Tuft cell T2R functionality and Th2 sinonasal inflammation, disease burden, and post-surgical outcomes in AERD patients. Aim 2: Determine if hyperfunctional Tuft cell T2Rs enhance denatonium-stimulated inflammatory responses in nasal epithelial air–liquid interface (ALI) cultures from AERD patients. Methods/Study Population: Aim 1: We will conduct a prospective cohort study with 82 AERD patients. Taste sensitivity to denatonium (DB), serving as a proxy for tuft cell T2R functionality, will be assessed using a validated 13-point scale, and correlations with clinical outcomes – SNOT-22, histopathologic, CT, and endoscopic scores – will be analyzed using linear regression. Aim 2: Sinonasal epithelial cells will be collected from AERD patients either hyper- or hyposensitive to DB and from healthy controls. We will establish ALI cultures and expose them to varying DB concentrations. Secretions will be analyzed for antimicrobial peptide release via bacterial kill assays and for IL-25 and β-defensin 2 via ELISA. Tuft cell frequency and baseline IL-25 mRNA expression will be assessed using immunofluorescence and quantitative real-time polymerase chain reaction, respectively. Results/Anticipated Results: We expect that higher DB taste sensitivity in AERD patients will correlate with worse clinical outcomes, reflected by elevated 6-month postoperative SNOT-22 scores, indicating increased symptoms. Additionally, we anticipate that preoperative Lund-MacKay and Lund-Kennedy scores, along with histopathological metrics, will be worse in DB-hypersensitive patients, establishing a link between taste sensitivity and disease burden. In vitro, we predict that AERD patients with DB hypersensitivity will demonstrate significantly higher IL-25 and β-defensin 2 secretion and reduced bacterial colonies in kill assays. We also expect increased tuft-cell frequency and baseline IL-25 mRNA in AERD-derived cultures compared to healthy controls, highlighting T2R functionality’s role in AERD pathogenesis. Discussion/Significance of Impact: This project aims to investigate a putative new role for Tuft cells in AERD pathogenesis by correlating Tuft cell T2R functionality with outcomes in AERD patients and with inflammatory response in vitro. Findings could lead to predictive clinical taste tests and future genotyping studies to identify T2R polymorphisms correlated with AERD severity.

Objectives/Goals: To assess the effect on the immune response to COVID-19 in children exposed to pesticides. The hypothesis is that increased pesticide exposure results in different immunological response to COVID-19. The goal of the proposal is to improve scientific knowledge on factors affecting COVID-19 and identify a modifiable factor to reduce these disparities. Methods/Study Population: A cross-sectional analysis of children (aged 5–17 years) with asthma to assess pesticide exposure and immune markers of SARS-CoV-2. SARS-CoV-2 infection or vaccination was determined with blood exposome RNA analyses assessed from blood samples taken at baseline. Immunological response was measured using neutralizing, phagocytizing, and NK-activating antibody responses biomarkers using plasma antibody isotyping, effector functions, T-cell activation-induced marker (AIM), and recall cytokine secretion assays on lysed, whole blood. Pesticide exposure was assessed as concentration of four urinary metabolites in a spot urine sample adjusted for creatinine. Unadjusted regression models were created to assess the effect of 3-phenoxy benzoic acid, a common pyrethroid pesticide, on immune markers. Results/Anticipated Results: Children’s (N = 30) average age was 10 years (interquartile range: 8–11) A majority of children were male (63%) and Non-Hispanic Black (73%). The majority of children had markers of SARS-CoV-2 infection (77%). Of the 4 pesticide metabolites assessed, only 3-PBA was commonly found (77% of samples > LOQ). Higher urinary concentrations of 3-PBA are associated with a significant (p Discussion/Significance of Impact: Significant associations in cytokine and inflammatory marker may indicate a Th2-skewed response, and dysregulated cytokine responses can lead to severe disease. A suggested increase in T-cell activation markers (e.g., CD4, CD8) may indicate potential exhaustion if excessively activated.

Objectives/Goals: Urinary tract infections (UTIs) cause significant morbidity, and many patients require multiple courses of antibiotics increasing the risk of antibiotic resistance. We determined the prevalence of urinary antibiotic heteroresistance (HR), which has been associated with treatment failures in vivo, to three first-line antibiotics for UTIs. Methods/Study Population: Clinical urine Escherichia coli isolates from patients in metropolitan Atlanta, Georgia in August 2023 were collected as part of public health surveillance performed by the CDC-funded, Georgia Emerging Infections Program (EIP). Only the first E. coli isolate collected for each patient was included in this study. Antibiotic susceptibility was determined through medical record review. HR to nitrofurantoin, trimethoprim-sulfamethoxazole, and fosfomycin was determined by population analysis profiling (PAP), where broth dilutions of E. coli were plated on increasing concentrations of the antibiotic. HR was defined as survival of >1 in 106 cfu but fewer than 50% survival at 1X antibiotic breakpoint (bp), resistant as > 50% survival at 1X bp and susceptible as survival of Results/Anticipated Results: Among 355 patients, 21 (5.9%) were resistant or intermediate to nitrofurantoin and 92 (26%) were resistant to trimethoprim-sulfamethoxazole. Antibiotic susceptibility data were missing from 5(1.4%) and 11(3%) of isolates for nitrofurantoin and trimethoprim-sulfamethoxazole, respectively. Susceptibility testing was not routinely performed nor reported for fosfomycin, thus excluded. PAP revealed that of the total 355 isolates, 3(0.84%) were heteroresistant to nitrofurantoin, 17(4.8%) were heteroresistant to trimethoprim-sulfamethoxazole, and 27(7.6%) were heteroresistant to fosfomycin. Of the isolates found to be susceptible by standard testing, 1(0.3%) and 9(3.6%) were heteroresistant to nitrofurantoin and trimethoprim-sulfamethoxazole by PAP, respectively. Discussion/Significance of Impact: Despite low rates of HR to nitrofurantoin and trimethoprim-sulfamethoxazole (0.84%, 4.8%), HR to fosfomycin was more frequent (7.6%). Given that susceptibility is not generally performed for fosfomycin, this could have implications for including fosfomycin as a first-line treatment for E. coli UTIs.

Objectives/Goals: Transmission-blocking vaccines hold promise for malaria elimination by reducing community transmission. But a major challenge that limits the development of efficacious vaccines is the vast parasite’s genetic diversity. This work aims to assess the genetic diversity of the Pfs25 vaccine candidate in complex infections across African countries. Methods/Study Population: We employed next-generation amplicon deep sequencing to identify nonsynonymous single nucleotide polymorphisms (SNPs) in 194 Plasmodium falciparum samples from four endemic African countries: Senegal, Tanzania, Ghana, and Burkina Faso. The individuals aged between 1 and 74 years, but most of them ranged from 1 to 19 years, and all presented symptomatic P. falciparum infection. The genome amplicon sequencing was analyzed using Geneious software and P. falciparum 3D7 as a reference. The SPNs were called with a minimum coverage of 500bp, and for this work, we used a very sensitive threshold of 1% variant frequency to determine the frequency of SNPs. The identified SNPs were threaded to the crystal structure of the Pfs25 protein, which allowed us to predict the impact of the novel SNP in the protein or antibody binding. Results/Anticipated Results: We identified 26 SNPs including 24 novel variants, and assessed their population prevalence and variant frequency in complex infections. Notably, five variants were detected in multiple samples (L63V, V143I, S39G, L63P, and E59G), while the remaining 21 were rare variants found in individual samples. Analysis of country-specific prevalence showed varying proportions of mutant alleles, with Ghana exhibiting the highest prevalence (44.6%), followed by Tanzania (12%), Senegal (11.8%), and Burkina Faso (2.7%). Moreover, we categorized SNPs based on their frequency, identifying dominant variants (>25%), and rare variants (Discussion/Significance of Impact: We identified additional SNPs in the Pfs25 gene beyond those previously reported. However, the majority of these newly discovered display low variant frequency and population prevalence. Further research exploring the functional implications of these variations will be important to elucidate their role in malaria transmission.

Objectives/Goals: Discriminatory experiences within healthcare settings significantly hinder equitable health access for sexual minority groups (SMPs) in the USA. These discriminatory experiences can manifest in various forms (e.g., refusal of care). We aimed to explore different types of discrimination encountered by SMPs in the healthcare settings. Methods/Study Population: This study utilized secondary data from the NIH All of Us Research Program. For this analysis, we selected cohorts self-identifying as gay (n  =  9,454), bisexual (n  =  15,284), lesbian (n  =  5,267), and straight (n  =  349,748), enabling robust comparisons across SMPs and straight individuals. We employed analysis of variance and Chi-square analyses to assess group differences in healthcare discrimination, using key indicators from the Discrimination in Medical Settings Scale. These indicators captured experiences such as being treated with less respect or courtesy and feeling ignored by healthcare providers, providing a comprehensive view of discriminatory encounters in healthcare settings for SMPs. Results/Anticipated Results: Our analyses revealed that bisexual individuals reported the highest levels of healthcare discrimination (mean  =  3.64, SD  =  2.45), followed by lesbians (mean  =  3.37, SD  =  2.47), other SMPs (mean  =  3.36, SD  =  2.53), gay (mean  =  2.69, SD  =  2.47), and straight participants (mean  =  2.60, SD  =  2.42). Among the seven discrimination indicators, the most reported experience was feeling like a doctor or nurse was not listening, with 76.8% of bisexual participants, 72.3% of lesbians, 68.8% of other SMPs, and 56.9% of gay participants reporting this experience. This was followed by reports of being treated with less respect and being treated with less courtesy in healthcare settings. These findings highlight the pervasive nature of healthcare discrimination among SMPs, particularly bisexual individuals. Discussion/Significance of Impact: SMPs experience higher levels of discrimination in healthcare settings compared to their straight counterparts. Our results underscore the urgent need to foster respectful, inclusive healthcare environments and ensure that healthcare providers are adequately trained to address the unique health needs and experiences of SMPs.

Objectives/Goals: Sexual minority populations (SMPs), including lesbian, gay, and bisexual groups, disproportionately encounter discriminatory experiences due to bi/homonegativity and systemic inequities across various social domains. We aim to understand how the neighborhood-level stressors and resilience sources differed across specific groups in SMPs. Methods/Study Population: Utilizing the NIH All of Us’ cloud-based platform, we selected cohorts self-identifying as gay (n  =  9,454), bisexual (n  =  15,284), lesbian (n = 5267), or straight (n  =  349,748). We explored multiple key measures of neighborhood-level stressors (e.g., neighborhood disorder, neighborhood cohesion, and environment index) and resilience sources (e.g., neighbor cohesion, social support), and other factors (e.g., food insecurity, housing insecurity, and housing instability) by their sexual orientations using analysis of variance or Chi-square analyses. Results/Anticipated Results: Our sample comprised 60.8% females and 37.5% males identifying as non-binary or transgender, with an average age of 55.6 years (SD  =  17.1). The racial composition was 56.0% White, 19.4% Black, 18.7% Hispanic, and 5.9% others (e.g., Asian, multiracial). Compared to straight individuals, SMPs reported high neighborhood stressors (e.g., disorder, worse environment) but lower neighborhood-level resilience sources (e.g., social support, cohesion). In addition, bisexual groups reported highest prevalence of housing insecurity (6.7% vs. 2.3%), housing instability (36.0% vs. 19.6%), and food insecurity (26.57% vs. 12.21%). Discussion/Significance of Impact: SMPs, particularly bisexual individuals, face greater neighborhood stressors and fewer resilience sources than their straight counterparts. These findings call for targeted interventions to address these disparities and promote health equity, using large-scale datasets to inform community-based solutions.

Objectives/Goals: This study looks to investigate the relationship between body mass index (BMI) and the treatment effect of cancer immunotherapies. Specifically, we will assess whether there is a significant difference in survival curves associated with varying BMI levels and track trends in BMI reporting over the last decade. Methods/Study Population: An individual patient meta-analysis will be conducted by reanalyzing raw data of phase 3 cancer immunotherapy trials (2013–2023) accessed via the database Vivli. Prior to making a formal data request, an exploratory search will be first done through clinicaltrials.gov to assess viability. Studies that report baseline BMI and treatment efficacy will be included. BMI will be analyzed as a continuous variable, with survival curves compared across different BMI ranges using restricted mean survival time and log-rank tests. Trials will be stratified by drug class and adjusted for race, age, and gender to account for potential sources of confounding/bias. Results/Anticipated Results: Results are currently still a work in progress as I am in the process of getting the dataset from Vivli. I anticipate that treatment effects in cancer immunotherapies will vary significantly by BMI. Furthermore, I expect to see significant disparities in survival outcomes between patients assigned to a low and high BMI category. Lastly, trends in the reporting of BMI across immunotherapy trials are expected to be inconsistent which highlights the need for more standardization in clinical trial datasets. Discussion/Significance of Impact: This study should address critical knowledge gaps in how BMI level is associated with immunotherapy outcomes. These findings could potentially guide personalized treatment strategies and highlight the importance of standardizing the variables clinical trials chose to report.

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: Male urogenital tract development is influenced by hormonal signals, which may be disrupted by endocrine-disrupting chemicals like lead. This observational study investigates the potential link between lead exposure and hypospadias rates in Puerto Rican boys, focusing on regional hotspots of hypospadias. Methods/Study Population: Lead levels from water plants across Puerto Rico were analyzed using PR Aqueduct and Sewer Authority water quality certificates. Hypospadias rates in seven health regions were obtained from the Puerto Rico Department of Health’s Birth Defects Prevention and Surveillance System. Data were from Puerto Rican boys born to women aged 15 years or older from 2017 to 2022. Rates were calculated using 2020 Census data, and statistical analyses were conducted using Intellectus. Results/Anticipated Results: Significant differences in hypospadias rates and lead levels were found across health regions, with the highest rates observed in Bayamón and Arecibo (5 cases per-100,000 births). Bayamón had the highest average lead concentration (14.33 ppb). A Kruskal–Wallis test showed significant regional variation in lead levels (χ²(6)  =  16.82, p  =  0.010) and hypospadias rates (χ²(6)  =  16.53, p  =  0.011). Post hoc analyses revealed key differences between regions, notably Bayamón and Metro. Discussion/Significance of Impact: These findings suggest a potential spatial link between prenatal lead exposure and hypospadias risk, underscoring the need for targeted public health interventions. Future studies will explore anti-Müllerian hormone expression in lead-exposed Sertoli cells to better understand the biological mechanisms behind these patterns.

Objectives/Goals: Mathematical models of airborne virus transmission lack supporting field and clinical data such as viral aerosol emission rates and airborne infectious doses. Here, we aim to measure inhalation exposure to influenza aerosols in a room shared with persons with community-acquired influenza and estimate the infectious dose via inhalation. Methods/Study Population: We recruited healthy volunteer recipients and influenza donors with polymerase chain reaction (PCR)-confirmed community-acquired infection. On admission to a hotel quarantine, recipients provided sera to determine baseline immunity to influenza virus, and donor infections were confirmed by quantitative real-time polymerase chain reaction. Donors and recipients were housed in separate rooms and interacted in an “event room” with controlled ventilation (0.2 – 0.5 air changes/hour) and relative humidity (20–40%). We collected ambient bioaerosol exposure samples using NIOSH BC-251 samplers. Donors provided exhaled breath samples collected by a Gesundheit-II (G-II). We analyzed aerosol samples using dPCR and fluorescent focus assays for influenza A and sera by hemagglutinin inhibition assay (HAI) against donor viruses and vaccine strains. Results/Anticipated Results: Among two cohorts (24b and 24c), we exposed 11 recipients (mean age: 36; 55% female) to 5 donors (mean age: 21; 80% female) infected with influenza A H1N1 or H3N2. Eight G-II and two NIOSH bioaerosol samples (1–4 µm and ≥4 µm) were PCR positive. We cultured virus from one G-II sample. Based on previous literature, we hypothesized that ~50% of immunologically naïve people (HAI Discussion/Significance of Impact: We demonstrated that it is feasible to recruit donors with community-acquired influenza and expose recipients to measurable virus quantities under controlled conditions. However, baseline immunity was high among volunteers. Our work sets the stage for designing studies with increased sample sizes comprising immunologically naïve volunteers.

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.