Exclusion of special populations (older adults; pregnant women, children, and adolescents; individuals of lower socioeconomic status and/or who live in rural communities; people from racial and ethnic minority groups; individuals from sexual or gender minority groups; and individuals with disabilities) in research is a pervasive problem, despite efforts and policy changes by the National Institutes of Health and other organizations. These populations are adversely impacted by social determinants of health (SDOH) that reduce access and ability to participate in biomedical research. In March 2020, the Northwestern University Clinical and Translational Sciences Institute hosted the “Lifespan and Life Course Research: integrating strategies” “Un-Meeting” to discuss barriers and solutions to underrepresentation of special populations in biomedical research. The COVID-19 pandemic highlighted how exclusion of representative populations in research can increase health inequities. We applied findings of this meeting to perform a literature review of barriers and solutions to recruitment and retention of representative populations in research and to discuss how findings are important to research conducted during the ongoing COVID-19 pandemic. We highlight the role of SDOH, review barriers and solutions to underrepresentation, and discuss the importance of a structural competency framework to improve research participation and retention among special populations.

OBJECTIVES/GOALS: Using the covariate-rich Veteran Health Administration data, estimate the association between Proton Pump Inhibitor (PPI) use and severe COVID-19, rigorously adjusting for confounding using propensity score (PS)-weighting. METHODS/STUDY POPULATION: We assembled a national retrospective cohort of United States veterans who tested positive for SARS-CoV-2, with information on 33 covariates including comorbidity diagnoses, lab values, and medications. Current outpatient PPI use was compared to non-use (two or more fills and pills on hand at admission vs no PPI prescription fill in prior year). The primary composite outcome was mechanical ventilation use or death within 60 days; the secondary composite outcome included ICU admission. PS-weighting mimicked a 1:1 matching cohort, allowing inclusion of all patients while achieving good covariate balance. The weighted cohort was analyzed using logistic regression. RESULTS/ANTICIPATED RESULTS: Our analytic cohort included 97,674 veterans with SARS-CoV-2 testing, of whom 14,958 (15.3%) tested positive (6,262 [41.9%] current PPI-users, 8,696 [58.1%] non-users). After weighting, all covariates were well-balanced with standardized mean differences less than a threshold of 0.1. Prior to PS-weighting (no covariate adjustment), we observed higher odds of the primary (9.3% vs 7.5%; OR 1.27, 95% CI 1.13-1.43) and secondary (25.8% vs 21.4%; OR 1.27, 95% CI 1.18-1.37) outcomes among PPI users vs non-users. After PS-weighting, PPI use vs non-use was not associated with the primary (8.2% vs 8.0%; OR 1.03, 95% CI 0.91-1.16) or secondary (23.4% vs 22.9%;OR 1.03, 95% CI 0.95-1.12) outcomes. DISCUSSION/SIGNIFICANCE: The associations between PPI use and severe COVID-19 outcomes that have been previously reported may be due to limitations in the covariates available for adjustment. With respect to COVID-19, our robust PS-weighted analysis provides patients and providers with further evidence for PPI safety.

Understanding place-based contributors to health requires geographically and culturally diverse study populations, but sharing location data is a significant challenge to multisite studies. Here, we describe a standardized and reproducible method to perform geospatial analyses for multisite studies. Using census tract-level information, we created software for geocoding and geospatial data linkage that was distributed to a consortium of birth cohorts located throughout the USA. Individual sites performed geospatial linkages and returned tract-level information for 8810 children to a central site for analyses. Our generalizable approach demonstrates the feasibility of geospatial analyses across study sites to promote collaborative translational research.

Extinction is the complete loss of a species, but the accuracy of that status depends on the overall information about the species. Dracaena umbraculifera was described in 1797 from a cultivated plant attributed to Mauritius, but repeated surveys failed to relocate it and it was categorized as Extinct on the IUCN Red List. However, several individuals labelled as D. umbraculifera grow in botanical gardens, suggesting that the species’ IUCN status may be inaccurate. The goal of this study was to understand (1) where D. umbraculifera originated, (2) which species are its close relatives, (3) whether it is extinct, and (4) the identity of the botanical garden accessions and whether they have conservation value. We sequenced a cpDNA region of Dracaena from Mauritius, botanical garden accessions labelled as D. umbraculifera, and individuals confirmed to be D. umbraculifera based on morphology, one of which is a living plant in a private garden. We included GenBank accessions of Dracaena from Madagascar and other locations and reconstructed the phylogeny using Bayesian and parsimony approaches. Phylogenies indicated that D. umbraculifera is more closely related to Dracaena reflexa from Madagascar than to Mauritian Dracaena. As anecdotal information indicated that the living D. umbraculifera originated from Madagascar, we conducted field expeditions there and located five wild populations; the species’ IUCN status should therefore be Critically Endangered because < 50 wild individuals remain. Although the identity of many botanical garden samples remains unresolved, this study highlights the importance of living collections for facilitating new discoveries and the importance of documenting and conserving the flora of Madagascar.

Silver Lake is the modern terminal playa of the Mojave River in southern California (USA). As a result, it is well located to record both influences from the winter precipitation dominated San Bernardino Mountains – the source of the Mojave River – and from the late summer to early fall North American monsoon at Silver Lake. Here, we present various physical, chemical and biological data from a new radiocarbon-dated, 8.2 m sediment core taken from Silver Lake that spans modern through 14.8 cal ka BP. Texturally, the core varies between sandy clay, clayey sand, and sand-silt-clay, often with abrupt sedimentological transitions. These grain-size changes are used to divide the core into six lake status intervals over the past 14.8 cal ka BP. Notable intervals include a dry Younger Dryas chronozone, a wet early Holocene terminating 7.8 – 7.4 cal ka BP, a distinct mid-Holocene arid interval, and a late Holocene return to ephemeral lake conditions. A comparison to potential climatic forcings implicates a combination of changing summer – winter insolation and tropical and N Pacific sea-surface temperature dynamics as the primary drivers of Holocene climate in the central Mojave Desert.