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.

The Weill Cornell Heart to Heart Community Outreach Campaign (H2H) is a free outreach program that provides mobile health screenings. The program brings medical and nursing faculty and students to the underserved, uninsured communities of New York City. Participants are screened for diabetes and heart disease risk factors through onsite exams, including point of care blood tests. If an abnormality is found, they receive a medical consultation to offer personalized advice and referrals to free/low-cost clinics when needed. The goal is to help underserved individuals understand their cardiometabolic health and to promote early intervention. This article describes the development of the program, including factors that were essential to the collaboration, challenges faced, barriers to implementation, and its evolution throughout the first 12 years. The program has benefited from strong foundational program leadership, effective inter-institutional collaboration, and maintaining community trust.

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.

This article describes lessons learned from the incorporation of language justice as an antiracism praxis for an academic Center addressing cardiometabolic inequities. Drawing from a thematic analysis of notes and discussions from the Center’s community engagement core, we present lessons learned from three examples of language justice: inclusion of bilingual team members, community mini-grants, and centering community in community-academic meetings. Facilitating strategies included preparing and reviewing materials in advance for interpretation/translation, live simultaneous interpretation for bilingual spaces, and in-language documents. Barriers included: time commitment and expenses, slow organizational shifts to collectively practice language justice, and institutional-level administrative hurdles beyond the community engagement core’s influence. Strengthening language justice means integrating language justice institutionally and into all research processes; dedicating time and processes to learn about and practice language justice; equitably funding language justice within research budgets; equitably engaging bilingual, bicultural staff and language justice practitioners; and creating processes for language justice in written and oral research and collaborative activities. Language justice is not optional and necessitates buy-in, leadership, and support of community engagement cores, Center leadership, university administrators, and funders. We discuss implications for systems and policy change to advance language justice in research to promote health equity.

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.

Clinical trials have provided evidence for determining treatment effectiveness. However, clinical trial participants have been underrepresented by diverse and special population groups (e.g., younger and older adults, different races/ethnicities), contributing to disparities in our understanding of diseases and treatments in all those affected. Addressing these disparities in clinical trial participation would be critical to achieving health equity in the USA and beyond. To assess enrollment inclusivity in clinical research at a large academic medical center in the southeast, we used administrative information to develop a snapshot of clinical research participation by age, sex, race, ethnicity, and rurality that was accessible to the public. We compared research enrollment statistics with relevant geographic benchmarks (county, state, and national) from the 2020 US Census. Comparisons revealed 1) over-participation by females relative to county, state, and national benchmarks; 2) under-representation of Black/African Americans relative to county, but higher relative to state and national, levels; and 3) underrepresentation of Hispanic/Latino and Asian groups. The ISP Snapshot has promoted accountability and transparency in this institution’s efforts toward health equity. The process has highlighted the need to update and standardize use of outdated categories (e.g., binary gender, rural status) that limit accurate reporting.

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.

Precision or “Personalized Medicine” and “Big Data” are growing trends in the biomedical research community and highlight an increased focus on access to larger datasets to effectively explore disease processes at the molecular level versus the previously common one-size-fits all approach. This focus necessitated a local transition from independent lab and siloed projects to a single software application utilizing a common ontology to create access to data from multiple repositories. Use of a common system has allowed for increased ease of collaboration and access to quality biospecimens that are extensively annotated with clinical, molecular, and patient associated data. The software needed to function at an enterprise level while continuing to allow investigators the autonomy and security access they desire. To identify a solution, a working group comprised of representation from independent repositories and areas of research focus across departments was established and responsible for review and implementation of an enterprise-wide biospecimen management system. Central to this process was the creation of a unified vocabulary across all repositories, including consensus around source of truth, standardized field definitions, and shared terminology.

There is a known disparity in clinical trial enrollment of rural-dwelling residents in the United States, largely due to financial constraints and travel burden. A big data study of an Intermountain West rural-serving healthcare system reported strong retention rates of historically underrepresented populations with adapted approaches. This exploratory qualitative descriptive study describes the lived experience and perceptions of eleven rural residents who participated or were interested in clinical trials from this healthcare system. Thematic analysis of interviews identified co-existing dualities between culture and traditional trial models, which suggest adapted designs are necessary to achieve opportunity equity in rural regions.

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.