Research Grants Program Office

Information on heat-related health risks that is based on meteorological data and forecasts is important for outdoor workers, farm managers, and many other stakeholders, but visualization and interpretation of climate data in a user-friendly way remains a challenge. This proof-of-concept research developed Sol, an artificial intelligence (AI) chatbot to conveniently interpret and communicate heat stress risks through smartphones and other devices. Sol is integrated into iHeatApp, a wet bulb globe temperature (WBGT) forecast visualization tool, to turn complex climate data into practical guidance with bilingual output in English and Spanish. The chatbot leverages an open source large language model (LLM) constrained by prompt engineering designs to reduce hallucinations and encourage domain-specific responses. The chatbot input may be either text or screenshot of the app's interface. Guided by our tutorial materials, we gathered farmworker feedback on the chatbot's ability to translate complex weather metrics into risk mitigation actions using focus groups of farmworkers from the Imperial Valley, California. When WBGT forecast values reach the “danger” category, the chatbot recommends wearing light, breathable clothing and increasing water breaks to prevent heat stress. Our app can help both farmworkers and their managers adapt work scheduling decisions to avoid the risks of peak heat and other health hazards and to mitigate labor productivity loss.

Objective: The number of missed school days attributable to secondhand smoke (SHS) exposure at home among U.S. children has not been quantified. We estimated the association between SHS exposure at home and school absenteeism and derived national estimates of SHS-attributable missed school days. Methods: We analyzed data from the 2016-2024 National Survey of Children's Health for U.S. children aged 6-11 years. Propensity score weighting and two-part models were used to estimate the association between SHS exposure at home and school absenteeism. National estimates of SHS-attributable missed school days were derived by combining model-based attributable fractions with national public school enrollment data. Results: SHS exposure at home was associated with both a higher likelihood of missing school and a greater number of missed school days among children with any absence. In 2024, an estimated 266,008 (95% CI: 139,627, 392,390) missed school days were attributable to SHS exposure at home nationwide, corresponding to 0.95 additional missed school days per exposed child (95% CI: 0.56, 1.34). Conclusions: This study provides the first national estimates of SHS-attributable missed school days among U.S. children. These findings suggest that reducing children's SHS exposure may further improve school attendance and promote more efficient use of educational resources.

OBJECTIVE: Nicotine and cannabis vaping are increasingly prevalent among young adults, and aiding sleep is a common reason for cannabis use. This study examined relationships between daily nicotine/cannabis vaping patterns and sleep. METHODS: From 2023 to 2024, 111 California young adults (aged 18-29; mean age = 23.9±3.0; 64% female; 31.5% non-Hispanic White) who vaped nicotine/cannabis ≥20 days/month completed 30 consecutive days of smartphone-based surveys. Self-reported sleep outcomes included 1) sleep duration (inadequate <7 versus adequate ≥7 hours) and 2) sleep quality (0=terrible to 10=excellent). Daily vaping patterns were non-vaping, nicotine-only vaping, cannabis-only vaping, or same-day co-vaping. Generalized mixed-effects models examined day-level associations between vaping patterns and sleep that night, adjusting for other substance use and baseline covariates. RESULTS: Of 2147 daily assessments, 51.7% reported inadequate sleep; mean sleep quality was 6.1±2.1. Nicotine-only vaping was most frequently reported (42.5% of the days), followed by same-day co-vaping (32.1%), non-vaping (16.1%), and cannabis-only vaping (9.3%). Nicotine-only vaping days had greater odds of inadequate sleep versus non-vaping (OR=1.40, 95%CI: 1.01-1.94) and versus cannabis-only days (1.93 [1.31-2.85]). Days with same-day co-vaping had greater odds of inadequate sleep compared with cannabis-only vaping (1.50 [1.01-2.23]). Associations between sleep quality and daily vaping patterns were not statistically significant. CONCLUSIONS: Nicotine vaping was associated with inadequate sleep duration compared to non-vaping or cannabis-only vaping. Despite perceptions of cannabis as a sleep aid, cannabis vaping did not improve sleep quality compared to non-vaping. These findings highlight the need for educational efforts or interventions addressing sleep health among young adults who vape nicotine and/or cannabis.

BackgroundDioxins are persistent environmental pollutants found in industrial emissions, tobacco smoke, and air pollution. Chronic exposure is associated with cardiovascular disease, but how dioxins act within the vessel wall to promote atherosclerosis remains unclear. We aimed to determine how dioxin exposure alters vascular smooth muscle cell behavior and whether smooth muscle cell aryl hydrocarbon receptor signaling modifies plaque progression.MethodsWe studied atherosclerotic mouse models exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin and complementary cultures of human coronary artery smooth muscle cells. We used single-cell gene-expression profiling, single-cell chromatin-accessibility profiling, smooth muscle cell lineage tracing, histology, cell migration and proliferation assays, and chromatin binding analysis.ResultsHere we show that dioxin exposure accelerates atherosclerosis, increases plaque size, promotes early smooth muscle cell phenotypic transitions, and enhances inflammatory cell recruitment. Modulated smooth muscle cells emerge as the most transcriptionally responsive vascular cell type to dioxin and important inflammatory mediators within plaques. Dioxin-induced gene programs overlap with tobacco-associated responses and are enriched for migration, inflammation, and cell-death pathways. Dioxin also increases chromatin accessibility at vascular remodeling and immune activation genes and reduces genomic binding of TCF21, a regulator of smooth muscle cell stability. Loss of aryl hydrocarbon receptor signaling specifically in smooth muscle cells worsens dioxin-induced plaque growth, oxidative stress, and loss of smooth muscle cell-derived fibrous cap cells.ConclusionsThese findings identify smooth muscle cell reprogramming as a mechanism by which dioxin promotes atherosclerosis and vascular inflammation. They also reveal that endogenous smooth muscle cell aryl hydrocarbon receptor signaling protects against oxidative stress and helps preserve plaque-stabilizing fibrous cap structure.

Abstract The atmospheric aging of nicotine-containing e-cigarette aerosols in the presence of nitrogen dioxide (NO2) and ozone (O3) may significantly alter their chemical composition and toxicological properties. However, the chemical transformation of nicotine within the complex e-cigarette aerosol matrix and its interaction with atmospheric oxidants remain largely uncharacterized. This study investigated the formation of tobacco-specific nitrosamines (TSNAs) from the aging of nicotine in e-cigarette aerosols exposed to NO2 and O3. We observed that NO2 facilitates the formation of N′-nitrosonornicotine (NNN) through direct nitrosation pathways, whereas O3 alone does not significantly contribute to TSNA production. In contrast, the presence of both oxidants enhanced the formation of nicotine-derived nitrosamine ketone (NNK), suggesting that oxidative transformation of nicotine plays an important role in its formation. FIGAERO-ToF-CIMS measurements identified several nicotine transformation products in aged e-cigarette aerosols that are not present in the fresh emissions, indicating chemical transformation during aging. Furthermore, long-amplicon qPCR analysis revealed that BEAS-2B cells exposed to aged aerosols experienced increased DNA damage, demonstrating enhanced genotoxic potential relative to their fresh counterparts. These findings indicate that atmospheric aging can convert nicotine into carcinogenic TSNAs and other reactive intermediates, increasing the potential health risks associated with secondhand and thirdhand vaping exposure. This work highlights the importance of considering chemically aged aerosols when evaluating the toxicity of e-cigarette emissions.

Do electric vehicles (EVs), and the expansion of curbside charging infrastructure in particular, undermine efforts to reduce vehicle travel? As EVs gain market share, decisionmakers may be less inclined to support policies such as bicycle lanes and reduced parking if they compete for space with EV chargers. We find no evidence, however, of policy substitution. Surveys in Los Angeles indicate that public support for policies to reduce driving is not swayed by the availability of EV charging. Furthermore, interviews in North American cities reveal that local officials are cautious about locking in scarce curbspace for EVs, and universally prioritized curb uses such as bicycle and bus lanes, street trees, and parklets. In our sample of early adopter cities, EV charging is not currently diminishing the political will for policies to reduce driving. However, this caution has slowed the rollout of curbside charging in North America.

Abstract Heavily managed urban streams, agricultural drainages, and least modified natural streams are rarely analyzed within a single framework, even though modern landscapes include a mix of them. Urbanization, agriculture, deforestation, mining, and other intensive land uses have dramatically altered fluvial systems. Most existing stream classification frameworks were developed for natural streams and rely only on natural geomorphic attributes. The few that address artificial streams focus exclusively on engineered (artificial) characteristics and usually address only a single land-use setting. As a result, these frameworks do not capture the full diversity of stream conditions found in mixed land-use watersheds that are influenced by both natural processes and human interventions. Recognizing this problem, our study proposes a joint geomorphic classification framework that collects and analyzes field data that captures both engineering and geomorphic attributes of streams in mixed land-use watersheds. We implemented this joint framework in a prime example of a mixed land-use watershed—the San Francisco Bay Area, California, USA. We collected a dataset for 164 stream sites. By using hierarchical cluster analysis on 92 variables computed from the field data, we identified 12 regional stream types, including six artificial and six natural ones. Our results demonstrate that this joint framework differentiates unique natural and artificial stream types in urban, agricultural, and wilderness settings. It also captures the subtle internal variability within artificial and natural stream types. Field photograph interpretation corroborates statistical findings that the diverse variables effectively represent real-world conditions of both types. Overall, by blending natural characteristics and the degree of human intervention, our classification provides critical insights that enhance our ability to understand river behavior in heavily managed urbanized, agricultural, and wilderness regions. It holds significant promise for informing targeted restoration and conservation strategies, ultimately contributing to more effective river management and sustainable watershed planning.

BACKGROUND: We conducted a randomized, double-blinded pilot trial to compare the impact of 2 electroacupuncture (EA) regimens on co-occurring neuropsychiatric symptoms among breast cancer survivors. METHODS: Breast cancer survivors (BCS) who self-reported cognitive impairment, fatigue, insomnia, or psychological distress were randomized (1:1) to receive 10 weekly EA to target either neuropsychiatric-specific (neuropsychiatric-specific EA, nEA) or nonneuropsychiatric-specific (sham EA, sEA) acupoints. Primary endpoints were the within-group pre-post effect sizes (Glass's Δ) in symptom severities, adjusted for multiple comparisons (Padjusted). Outcomes were assessed using neurocognitive tests (CANTAB), patient-reported outcomes (PROs) (Functional Assessment of Cancer Therapy-Cognitive Function, Multidimensional Fatigue Symptom Inventory-Short Form, European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core 30), plasma biomarkers, and neuroimaging. Responders were defined by reliable change index (for objective cognition) or minimal clinically important differences (for PROs). RESULTS: Thirty-five participants were recruited, with 30 (86%) completing all sessions. The mean (±SD) age was 58.2 (±12.2) years, and 86% reported co-occurring symptoms. Following treatment, the nEA group demonstrated significant improvements in attention (T3: Δ = 0.562, T4: Δ = 0.708, both Padjusted <.05) and distress (T3: Δ = 0.764, T4: Δ = 0.711, both Padjusted < .05). More responders were observed after nEA treatment for objective cognition (42.9% vs 12.5%) and distress (50% vs 37.5%). Neuropsychiatric-specific EA-treated participants showed increased gray matter volume compared with sEA (P = .033), which positively correlated with better attention function (r = 0.69, P = .020). Neuropsychiatric-specific EA-related improvements in memory and response speed were associated with reduced connectivity in the default mode network (DMN-SFG, r = -0.93, P < .01) and increased connectivity in the dorsal attention network (DAN-SMG, r = 0.86, P < .001), respectively. All adverse events were grade 2 or lower. CONCLUSION(S): Electroacupuncture targeting neuropsychiatric-specific acupoints suggests improvements in cognition and distress symptoms in BCS, warranting validation in larger, multicenter trials. CLINICALTRIALS.GOV: NCT05283577.

BACKGROUND: Safe passage interventions aim to enhance public safety and improve access to community resources, including public parks, in underserved communities. However, no studies have directly compared community- and police-led safety interventions with respect to park-based moderate to vigorous physical activity (MVPA). To address this gap, we compared associations between Community-led Safe Passage Services (SPS) and the Los Angeles Police Department Community Safety Partnership (CSP) program with MVPA in South Los Angeles public parks. METHODS: We conducted structured observations of 3997 park users across 8 SPS and 9 CSP parks in South Los Angeles using the System for Observing Play and Recreation in Communities and the Physical Activity Resource Assessment. We applied t tests, analysis of variance, and hierarchical linear models to examine MVPA across park intervention types. RESULTS: Overall, MVPA was higher in SPS parks (P < .001). Black, male, teen, and adult park users exhibited significantly higher MVPA in SPS parks (P < .001). A hierarchical linear model controlling for sex, age, race, and park conditions indicated that Black park users were significantly less physically active in CSP parks (P = .05). Conversely, Black park users had significantly higher MVPA in SPS parks (P = .034). Intervention type was a stronger predictor of MVPA than park features and amenities, whereas incivilities were negatively associated with MVPA (P < .001). CONCLUSIONS: Community-led safety interventions may promote physical activity among Black park users. These findings suggest that community-led public park safety models are a promising approach for advancing health equity.

BackgroundVeterans have a unique health profile and risk for substance use, but few studies compare cannabis use patterns among US military Veterans and non-veteran civilians.ObjectiveTo examine differences in age-specific patterns, modes of use, and sociodemographic correlates of cannabis use between Veterans and non-Veterans.Design, Participants, MeasuresWe conducted a cross-sectional analysis of Behavioral Risk Factor Surveillance System data from 2016 to 2023. The analytic sample included 907,136 adults aged 18 to 80 years with complete data on self-reported veteran status and cannabis use. Primary outcomes were past 30-day cannabis use (yes/no), frequency of use in the past 30 days, and inhalational vs. non-inhalational use methods. Multivariable logistic regressions were used to assess sociodemographic and behavioral correlates of cannabis use. Analyses were conducted from March to June 2025.ResultsAmong participants, 114,193 (12.6%) were Veterans. Although overall cannabis use was lower among Veterans than non-Veterans, age-specific patterns differed. Veterans aged 50–64 years were 43% (95% CI, 28–59%) more likely to report cannabis use than non-Veterans, and those aged 65–80 were 22% (95% CI, 9–37%) more likely. Older Veterans also reported more frequent cannabis use in the past 30 days (mean 18.4 versus 15.8 days among those aged 50–64 years; 17.3 vs. 14.5 days among those aged 65–80 years). Inhalational use was more common among Veterans than non-Veterans (90.0%; 95% CI, 87.8–91.9% vs. 83.7%; 95% CI, 82.5–84.9%). Some correlates of cannabis use were shared across groups; however, educational attainment was differentially associated with cannabis use by veteran status.ConclusionsVeterans aged ≥ 50 years were more likely to report cannabis use and used it more frequently than their non-veteran peers, suggesting they may need tailored interventions to address cannabis use.