Environment International

Background: Endocrine-disrupting chemicals (EDCs) in consumer products are ubiquitously detected in human biospecimens, yet most epidemiological studies examine single chemicals rather than real-world co-exposures. We evaluated associations between a mixture of seven urinary chemical biomarkers and systemic inflammation. Methods: Survey-weighted log-log regression models adjusted for age, sex, race/ethnicity, poverty-income ratio, and survey cycle were conducted with Benjamini-Hochberg FDR correction (primary analysis, N=4,864). A sensitivity analysis additionally adjusted for body mass index and smoking status (N=4,494). Results: In the primary analysis, 5 of 7 chemicals showed significant associations after FDR correction: ethylparaben ({beta} = -0.056, FDR P < .001), propylparaben ({beta} = -0.026, FDR P = .007), bisphenol A ({beta} = +0.052, FDR P = .005), monoethyl phthalate ({beta} = +0.043, FDR P = .002), and monocyclohexyl phthalate ({beta} = +0.215, FDR P = .007). The WQS mixture index was significantly associated with CRP ({beta} = +0.056, 95% CI [0.031, 0.081], P < .001), with monocyclohexyl phthalate carrying the largest mixture weight (0.342). In the BMI- and smoking-adjusted sensitivity analysis, associations attenuated to null for all chemicals, though MCP preserved direction ({beta} = +0.129) and the WQS mixture direction was maintained ({beta} = +0.018). Two multiple imputation sensitivity analyses confirmed that monocyclohexyl phthalate was the only chemical to maintain a positive direction across all four analytical specifications (primary complete-case, BMI-adjusted complete-case, primary-aligned imputation, and BMI-adjusted imputation), reaching statistical significance in three of four specifications and providing convergent evidence of a robust MCP-inflammation association. Conclusions: The chemical mixture showed a significant collective association with systemic inflammation, consistent with a cumulative pro-inflammatory burden from co-exposure to multiple consumer product chemicals. These findings suggest that regulatory approaches should shift from single-chemical to mixture-based risk assessment frameworks for consumer product safety.

Healthcare waste (HCW) management is a critical determinant of occupational safety, infection control, and environmental protection, particularly in low- and middle-income settings. Using the knowledge-attitude-practice (KAP) framework, this study assessed cognitive, behavioral, and institutional dimensions of HCW management among healthcare workers in urban Bangladesh. A cross-sectional survey was conducted among 342 cleaners and nurses in hospitals in the Chattogram Metropolitan Area (CMA) and Cumilla City Corporation (CuCC). Marked disparities were observed across professional groups. Training coverage was significantly lower among nurses than cleaners in CMA (22.5% vs. 48.7%; p = 0.002), whereas in CuCC nurses showed higher coverage (69.0% vs. 52.3%; p < 0.01). Knowledge of color-coded waste segregation was generally inadequate, with only 39.3% of CMA cleaners correctly identifying pharmaceutical waste bins compared with 60.0% of nurses (p < 0.01); CuCC nurses demonstrated substantially higher awareness (82.8%). Attitudinal indicators favored nurses, with strong hygiene and environmental risk awareness (95-100%) compared with cleaners (66-87.3%; p < 0.001). Despite this, compliance with segregation practices remained low across both sites (<30%). Several institutional support indicators were more favorable among nurses, particularly in CuCC. These findings indicate a significant knowledge-practice gap, emphasizing that effective HCW management requires not only training but also strengthened institutional structures and enforcement mechanisms to reduce public health and environmental risks.

Stress is a major risk factor for mental disorders, and urban living is a key environmental contributor. Nature exposure may promote stress recovery and mental health, but how physiological arousal and subjective stress change across green versus gray space during naturalistic urban mobility is poorly understood. This preregistered study (https://doi.org/10.17605/OSF.IO/HF4RW) employed geolocation-based ambulatory assessment to examine psychophysiological arousal and subjective stress during transitions between urban green and gray environments. Thirty-six healthy urban residents completed a counterbalanced circular walking route in Cologne, Germany, with continuous GPS, cardiovascular, and electrodermal recording alongside ecological momentary assessment of subjective stress, affect, and exertion. Green compared to gray spaces were associated with lower subjective stress and higher affective well-being, with cardiac indices reflecting reduced autonomic arousal during green space exposure. Autonomic changes surrounding environmental transitions persisted beyond the immediate transition window, suggesting that physiological benefits of green space exposure extend into subsequent gray environments. These findings underscore the public health potential of urban green infrastructure for preventing stress-related mental health conditions.

Inflammatory bowel diseases (IBD) affect millions of patients worldwide and impair quality of life. Although genetic and environmental factors are known to disrupt the gastrointestinal (GI) epithelial barrier and increase susceptibility to IBD, the precise contribution of specific environmental exposures remains unclear. Per- and polyfluoroalkyl substances (PFAS), or "forever chemicals," are widely used in consumer products and contaminate food and water sources, resulting in chronic oral exposure worldwide. Perfluorooctanoic acid (PFOA), a common PFAS, has been epidemiologically associated with the development of IBD, particularly in older adults. Here, we assessed the effects of oral PFOA exposure on the GI tract, liver, and susceptibility to colitis. C57BL/6 mice were exposed to PFOA (0.1 mg/kg or 1.0 mg/kg) beginning at weaning (post-natal day [P]21) for a time course of 4 or 8 weeks. GI physiology/pathology (Ussing chambers; histology), expression of pro-inflammatory cytokines (qPCR), microbiota composition (16S sequencing), bile acids production (qPCR; LC/MS), and liver pathology (histology) were assessed. Colitis susceptibility was evaluated in genetically predisposed (IL10 knockout) mice, and in induced (dextran sodium sulfate [DSS]) mouse models following PFOA exposure (8 weeks at 1.0 mg/kg). Oral PFOA exposure increased intestinal permeability, mildly increased cytokine expression, altered gut microbiota composition, disrupted liver and serum bile acids, and caused hepatic hypertrophy at higher doses and longer exposure. Although PFOA did not increase disease susceptibility in genetically predisposed Il10 KO mice, it significantly worsened DSS-induced colitis, but only in male mice. Together, these findings demonstrate that early-life PFOA exposure disrupts the gut-liver axis and may contribute to colitis development in a sex dependent manner.

Neonatal meconium provides a non-invasive matrix for assessing prenatal or near-birth exposure to environmental contaminants. Although microplastics and metals have each been reported in human biological samples, integrated assessments of concurrent particle and metal exposure in meconium remain scarce, particularly in South Asia. In this cross-sectional biomonitoring study, meconium from 30 Cesarean-delivered neonates born in Dhaka, Bangladesh, was analyzed for microplastic occurrence, morphology, and polymer composition using stereomicroscopy, scanning electron microscopy, and Raman spectroscopy, and for fifteen metals using inductively coupled plasma mass spectrometry. Maternal breast milk from a subset of lactating mothers was analyzed as a complementary maternal exposure context. Microplastics were detected in all analyzable meconium samples (n=28), with a median burden of 149 particles/g wet weight, dominated by polyethylene terephthalate fragments and nylon fibers. All fifteen measured metals were also detected in all analyzable meconium samples, with median Pb and Cr concentrations of 1.18 and 3.92 ug/g dry weight, respectively. No microplastic-metal associations remained significant after multiple-testing correction, suggesting partly distinct exposure or accumulation pathways. Here, we show that neonatal meconium captures concurrent microplastic and metal exposure in an urban South Asian birth cohort. This study provides one of the first integrated meconium-based assessments of concurrent microplastic and metal exposure from the region and highlights meconium as a practical matrix for early-life biomonitoring.

Early embryogenesis is governed by precisely timed gene regulatory programs that coordinate cell fate specification, tissue patterning, and morphogenesis. The maternal-to-zygotic transition (MZT) represents a pivotal developmental milestone during which regulatory control shifts from maternally deposited transcripts to activation of the zygotic genome. Disruption of this transition has the potential to alter developmental trajectories with lasting consequences. Per- and polyfluoroalkyl substances (PFAS), environmentally persistent contaminants, have been linked to developmental abnormalities, yet their impact on core embryonic gene regulatory networks especially during MZT is not well understood. Using zebrafish (Danio rerio), a tractable vertebrate model and New Approach Methodology (NAM), we investigated how PFAS exposure during the MZT alters early developmental programming. Embryos were exposed starting at different times within the 8-hour MZT window and collected at 24 hours post-fertilization (hpf) for transcriptomic analysis. Targeted qRT-PCR revealed dysregulation of genes controlling transcriptional activation, lineage specification, proliferation, and differentiation. Whole-transcriptome RNA sequencing (RNA-seq) further identified widespread perturbations in gene networks governing transcriptional regulation, cell signaling, and embryonic morphogenesis. Temporal analysis revealed that exposure beginning at 3.5 hpf, followed by 8 hpf, corresponding to early zygotic genome activation and near completion of zygotic activation, respectively, resulted in the greatest differential gene expression changes. Consistent with these early gene regulatory perturbations, larvae exposed at 8 hpf also exhibited altered behavior at 5 days post-fertilization. Together, these findings demonstrate that PFAS exposure during MZT disrupts the establishment of embryonic gene regulatory networks, linking environmental toxicant exposure to altered developmental patterning and organismal outcomes. This work underscores the vulnerability of early developmental transitions to environmental perturbation and positions MZT as a critical window of susceptibility during development.

Until now, there has been no animal-free alternative method for predicting chronic inflammation and delivering the associated dose responses, the timing of onset, and the duration of inflammation, as required by regulatory agencies. We present the results of pre-validation of an in-vitro-learned digital twin (InFiniteLungDT) capable of predicting chronic neutrophilic lung inflammation for regulatory use. The method is based on measuring the dynamics of early biological effects in vitro induced by respirable materials or their mixtures, without the need to know their intrinsic properties. We constructed the digital twin(s) for each of the material, for which we have in vivo exposure data. The instillation data set, comprising 49 different nanomaterials, was used as the primary anchor to calibrate the model. Inhalation data set, comprising 7 different nanomaterials, compliant with OECD TG 412, was used to show the general applicability of the method across species and for different exposure scenaria. In total, about 3094 single mouse exposures and 364 rat exposures (and approx. 775/225 non-exposed mouse/rat controls) were used to predict concentration-dependent time-evolved neutrophil influx into the lung. The accuracy (predictive capacity) of LOAEL determination is 93% for instillation and 84% for inhalation exposure. Taking into account the time-to-deliver-result being less than 1 week, this proves that the effect of inhaled material from acute to chronic conditions can be assessed orders of magnitude faster and cheaper than in a reference animal study.

The ubiquitously occurring food contaminants altenuene (ALT) and tentoxin (TEN) are recognized as emerging Alternaria mycotoxins, yet substantial data gaps remain when it comes to their toxicological behavior and toxicokinetic characteristics. This study aimed to compare and generate quantitative data on their hepatic metabolism and to obtain semi-quantitative insights into their metabolite profiles. To this end, primary rat and human hepatocytes were incubated with 10 {micro}M ALT or TEN over multiple time points up to 4 h. Both substrate depletion and metabolite identification revealed pronounced interspecies differences. The extent of ALT metabolism was significant, with an 88% and 57% decrease in rat and human hepatocytes after 4 h, respectively. In contrast, TEN showed extensive biotransformation in rats (67%) but only modest turnover in humans (27%) over the same period. Hepatocellular clearances were consistently higher for ALT than TEN, with hepatic extraction ratios indicating intermediate extraction for ALT and low extraction for TEN. High-resolution mass spectrometry combined with targeted analysis of selected metabolites annotated phase II conjugation as the predominant metabolic pathway for ALT and phase I oxidative metabolism for TEN, including mono- and double-metabolized species for the latter. Overall, these results provide a comprehensive characterization of ALT- and TEN-metabolism in hepatocytes, offering a foundation for future studies on their toxicological relevance and impact on human health.

Background Childhood overweight and obesity represent major public health challenges, shaped by socio-economic and environmental factors. This study investigates the mediating and moderating role of urban environmental exposures in socio-economic disparities in childhood excess weight. Methods Data was drawn from a population-based sample of children (2-9 years) and adolescents (10-17 years) living in Geneva, Switzerland. Parents reported household financial situation and children's height and weight, from which excess weight (i.e. overweight or obesity) was derived. Residential exposures to air pollution (PM2.5, NO2), noise (daytime, nighttime), and neighborhood greenness (green areas, canopy coverage) were estimated based on geocoded residential addresses. The association between household financial situation and excess weight was evaluated, as well as the mediating and moderating roles of urban environmental exposures. Results The analysis included 1006 children and 1154 adolescents. Among children, an average-to-poor household financial situation was associated with higher odds of excess weight in children (adjusted odds ratio [aOR]: 1.79, 95% confidence interval [CI]: 1.13; 2.84). Higher noise exposure was associated with excess weight (daytime: aOR: 1.40, 95% CI: 1.10; 1.77, nighttime: aOR: 1.37, 95% CI: 1.08; 1.74), while the association with PM2.5 appeared stronger among socio-economically disadvantaged children, though the interaction did not reach statistical significance (financial situation x PM2.5 interaction: aOR: 1.59, 95% CI: 0.98; 2.59). No significant associations were observed among adolescents. Conclusion These findings highlight the joint influence of social and environmental inequalities on childhood excess weight and stress the need to address these interconnected determinants to design equitable, targeted public health interventions.

The foodborne mycotoxins alternariol (AOH) and alternariol monomethyl ether (AME) have been associated with several adverse effects, including cytotoxicity, genotoxicity, endocrine disruption, and immunomodulation. As these endpoints are typically observed in vitro at micromolar concentrations, the question arises whether such levels are attainable in exposed humans. To address this data gap in chemical risk assessment, a physiologically based kinetic (PBK) model was developed to predict internal exposure doses to AOH and AME in humans. As input parameters, kinetic constants for hepatic glucuronidation were obtained in vitro by incubating Sprague Dawley rat and human liver S9 fractions with 0.5-50 M AOH and 0.5-20 M AME, demonstrating rapid biotransformation in both species. Intestinal absorption of AME and physicochemical parameters were estimated using quantitative structure-activity relationship (QSAR) models. Sensitivity analysis identified parameters describing hepatic glucuronidation and gastrointestinal uptake as among the most influential, confirming the importance of their reliable estimation. The PBK model was evaluated against available rodent toxicokinetic data and subsequently extrapolated to humans. Ultimately, the currently available exposure estimates published by EFSA in 2016 were applied to predict target tissue concentrations, which were compared to points of departure (PoDs) for relevant toxicological endpoints. Even in the most susceptible group of male toddlers, predicted internal concentrations (10-4 M range) were approximately four orders of magnitude below the respective PoDs. Consequently, under the applied exposure assumptions and considering the compounds as isolated chemicals, AOH and AME are not expected to reach systemic or tissue concentrations associated with the investigated effects.

BackgroundWildland firefighters experience repeated occupational exposure to wildfire smoke at high particulate matter (PM) concentrations, leading to elevated cardiovascular disease risk and hypertension prevalence. However, the pathophysiological processes linking cumulative smoke inhalation to vascular damage and blood pressure elevation remain poorly characterized. To evaluate these effects under controlled exposure conditions, we used a preclinical exposure model calibrated to match the cumulative PM burden deposited in wildland firefighter airways over 7-14 years of service. Male apolipoprotein E knockout (Apoe-/-) mice underwent whole-body inhalation of Douglas fir smoke or filtered air for 2 hours/day, 5 days/week, for 8 or 16 weeks at target PM concentrations of 40 mg/m3. ResultsProlonged smoke exposure induced sustained elevation of circulating tumor necrosis factor-alpha (TNF-), interleukin-1 beta (IL-1{beta}), and interleukin-6 (IL-6), coupled with diffused nuclear factor kappa B (NF-{kappa}B) activation throughout the aortic wall. Smoke inhalation disrupted endothelial adherens junctions, upregulated intercellular adhesion molecule-1 (ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1), and promoted monocyte recruitment to aortic tissues, concurrent with enhanced monocyte chemoattractant protein-1 (MCP-1) expression. Oxidative stress was evidenced by increased nicotinamide adenine dinucleotide phosphate (NADPH) oxidase subunit 2 (NOX2) expression, elevated superoxide levels, and endothelial nitric oxide synthase (eNOS) uncoupling in the aorta, leading to lipid peroxidation and accompanied by intimal apoptosis. These inflammatory and oxidative perturbations occurred alongside a pro-fibrotic phenotypic shift characterized by transforming growth factor beta 1 (TGF-{beta}1) upregulation, myofibroblast differentiation, and progressive collagen accumulation in medial and adventitial compartments of the aortic wall. Functionally, smoke exposure progressively impaired aortic cyclic distensibility through combined wall thickening and circumferential tissue stiffening, while severely attenuating endothelium-dependent and nitric oxide (NO)-mediated vasodilation. These functional and structural shifts culminated in elevated systolic and diastolic blood pressures. While endothelial dysfunction reached maximal impairment by 8 weeks, aortic stiffening continued to worsen through 16 weeks of exposure, demonstrating differential temporal progression of vascular damage. ConclusionsThese findings demonstrate that occupationally relevant wildfire smoke exposure produces convergent inflammatory, oxidative, and profibrotic vascular remodeling with progressive loss of arterial compliance and impaired endothelium-dependent vasodilation, underscoring potential vascular targets for cardiovascular health surveillance and risk mitigation in wildland firefighters.

In recent years, the synergistic role of endocrine-disrupting chemicals (EDCs) and gut microbiota in the development of diabetes has been increasingly documented in rodent models. However, most studies have focused on one or two EDCs with varying doses and exposure durations, limiting the identification of a shared microbial signature associated with EDC-induced glucose dysregulation. This meta-analysis aimed to identify a common gut microbiome pattern across rodent studies involving diverse EDC exposures linked to glucose dyshomeostasis. A systematic search yielded 3,748 studies, of which ten met the inclusion criteria, comprising sequence data from 189 samples. These studies evaluated gut microbiota alterations in diabetes induced by various EDCs, including pesticides, food additives, and heavy metals, across different exposure conditions. Meta-analysis revealed a consistent reduction in microbial diversity and an increased Firmicutes/Bacteroidetes ratio following EDC exposure. At the phylum level, Firmicutes, Proteobacteria, Desulfobacterota, and Patescibacteria were significantly enriched. Although beneficial genera such as Lactobacillus, Bifidobacterium, and Akkermansia showed a decreasing trend, these changes were not statistically significant. In contrast, xenobiotic-associated genera including Desulfovibrio, Pseudomonas, Parasutterella, and Candidatus Saccharimonas were significantly increased. Notably, sulfate-reducing bacteria were the only inflammation-associated group consistently elevated. These microbial alterations were distinct from those observed in high-fat diet-induced diabetic models. This study identifies a distinct gut microbiome signature associated with EDC exposure in rodent models of glucose imbalance. These findings suggest unique microbiome-mediated pathways in EDC-induced diabetes and highlight potential microbial targets for early intervention in environmentally driven metabolic disorders.

Background: Climate mitigation policies can lower air pollutant concentrations and deliver substantial health co-benefits. The French Ecological Transition Agency (ADEME) proposed four contrasting Transitions 2050 net-zero scenarios. We quantified mortality, morbidity, and health-economic co-benefits from projected PM2.5 and NO2 reductions across all four scenarios in continental France. Methods: Emission projections were input to the CHIMERE chemistry-transport model to estimate PM2.5 and NO2 concentrations for 2030 and 2050. Health impacts were assessed using disease-specific cessation-lag assumptions relative to 2019, covering premature mortality, morbidity, DALYs, and economic benefits across nine outcomes (hypertension, lung cancer, ischaemic heart disease, stroke, COPD, type-2 diabetes, acute lower respiratory infections, and asthma in children and adults). Findings: Population exposure is projected to decline by about 40% for PM2.5 and 70% for NO2 by 2050, with health gains remaining substantial and broadly equivalent across all four scenarios and modest differences between sufficiency-oriented and technology-driven pathways. Under delayed-impact assumptions, avoided premature deaths ranged from 21,300 to 22,100 for PM2.5 and 24,500 to 26,200 for NO2. Morbidity and disability-adjusted life year (DALY) reductions, as well as economic savings, spanned similarly; total avoided morbidity cases were 84,000-88,000, direct medical cost reductions were e1.0-1.1 billion/year, and intangible cost savings of e41-43 billion and e36-39 billion, respectively. Interpretation: Health co-benefits are substantial, consistent across contrasting scenarios, and increase markedly from 2030 to 2050. Explicitly incorporating these co-benefits into climate policy appraisals may strengthen the case for ambitious mitigation and improve decision-maker acceptability.

Fluorinated chemicals are increasingly prevalent in pharmaceuticals and agrochemicals, yet their influence on the human gut microbiome and the potential for microbial biotransformation to alter therapeutic and toxicological profiles remain poorly understood. Here, we investigated the bidirectional relationship between 15 structurally diverse fluorinated chemicals and the gut microbiota by using an ex vivo high-throughput fermentation system. Screening revealed that flutamide, fluazinam, and pretomanid were consistently biotransformed across the donor microbiomes, while other compounds showed substantial inter-individual variability in degradation. Furthermore, exposure to fluorinated chemicals induced compound-specific shifts in microbial diversity and community composition, demonstrating their capacity to alter gut microbial ecology. Using a computational workflow combining in silico biotransformation predictions with untargeted LC-MS/MS analysis, we identified nitroreduction as the primary gut microbial transformation across all three compounds. Single-strain experiments confirmed that the nitroreduction of flutamide to flu-6, previously attributed only to hepatic metabolism, is a widespread capacity among gut bacterial strains. Finally, in vitro cytotoxicity assays and in silico modelling further revealed flu-6 to be a less hepatotoxic derivative than the parent compound, suggesting a potential detoxifying role for the gut microbiota. Together, these findings establish an integrated ex vivo, in vitro, and in silico approach for assessing the bidirectional interactions between fluorinated chemicals and the gut microbiome.

Omics technologies are increasingly integrated into next-generation risk assessment, yet quantitative toxicogenomics outcomes remain highly dependent on analytical choices, motivating a systematic evaluation of how bioinformatics workflows influence hazard characterization and transcriptomic Points of Departure (tPOD). Here, we applied five independent transcriptomics pipelines to a shared dataset of RPTEC-TERT1 kidney cells exposed to cisplatin across multiple concentrations and timepoints, comparing effects of pre-processing, benchmark concentration modeling, and pathway-based interpretation strategies. Across workflows, substantial variability was observed in gene-level benchmark concentrations (BMCs), primarily driven by differences in normalization, filtering, and especially the modeling software used. Despite this variability, convergence increased at later timepoints as transcriptional responses strengthened, with 24 h consistently identified as the most sensitive timepoint at the gene level. Aggregation of gene-level BMCs into pathway-based metrics reduced variability but did not eliminate it, with pathway definition emerging as a major determinant of sensitivity estimates. Notably, distinct pathway resources showed minimal gene overlap, and smaller, biologically coherent gene sets (e.g., co-expression modules and biomarker panels) produced lower and less dispersed BMCs compared with broader pathway annotations. Furthermore, direct modeling of pathway activity scores yielded systematically different sensitivity estimates relative to median-based aggregation, with method-dependent conservativeness influenced by pathway coverage and response strength. Overall, our findings demonstrate that both analytical workflow design and pathway selection critically shape toxicogenomic-derived potency estimates, highlighting the need for harmonized, transparent methodologies to enable robust application of transcriptomics in chemical safety assessment and regulatory decision-making.

Background and Purpose: Ambient air pollution is an established risk factor for incident stroke, but whether post-discharge pollutant exposure influences stroke recurrence remains unknown. We investigated the association between post-discharge exposure to six ambient air pollutants and stroke recurrence in patients with acute ischemic stroke. Methods: We analyzed data from 27,346 patients in the CRCS-K-NIH nationwide multicenter registry of acute ischemic stroke patients (2014-2021) with confirmed ischemic stroke, residential address data, and matched air quality records. The primary exposure was the 3-month post-discharge average concentration of PM10, PM2.5, NO2, SO2, CO, and O2, assessed at the district level using inverse-distance weighted interpolation. The primary outcome was stroke recurrence from 3 to 15 months post-discharge. Cause-specific Cox proportional hazards models accounting for the multilevel data structure were used, with all-cause mortality as a competing risk. Restricted cubic splines assessed nonlinear dose-response relationships. Results: During follow-up (median 364.8 days), 765 patients experienced stroke recurrence and 471 died. Among the six pollutants, only SO2 showed a statistically significant association with recurrence (P for overall association in the restricted cubic spline analysis = 0.024). A potential threshold was identified at approximately 8.2 ppb, above which recurrence risk increased progressively (P for non-linearity = 0.095). The association was numerically stronger among older adults ([&ge;]75 years; P for interaction = 0.051) and women (P for interaction = 0.062). The highest SO2 concentrations were observed in harbor cities (Incheon, Ulsan, Busan), consistent with maritime shipping emissions. No significant associations were observed for the other five pollutants. Conclusions: Elevated post-discharge SO? exposure is associated with increased stroke recurrence risk, particularly in harbor regions and among older adults and women. These findings support incorporating ambient air quality monitoring into secondary stroke prevention strategies.

Since the 1950s, micro- and nanoplastics (MNPs) have become omnipresent, representing a novel environmental hazard which continually deposits in our airways. Pulmonary macrophages (pMacs) orchestrate the balance between inflammation and tolerance required for homeostasis of the lung and are among the first immune cells to encounter inhaled MNPs. Yet, how pMacs react to plastic deposition in the lung and implications for disease remain unknown. Here, we exposed mice in vivo, human precision-cut lung slices (hPCLS) ex vivo, and monocyte-derived macrophages and cell lines to polystyrene MNPs in vitro. MNP deposition in the lung and extrapulmonary tissues was determined over a 1-week period and pMacs from MNP-laden lungs isolated for RNA-sequencing. We compared the effects of MNPs or diesel exhaust particulate exposures on hPCLS viability and metabolism, monocyte-derived macrophage transcription, and macrophage mitochondrial function, inflammation, and antigen presentation. MNPs readily translocated the lung and were observed in all organs examined within 1-day. pMacs from MNP-exposed mice expressed transcriptional pathways associated with endocrine system disorders, tissue remodeling, and malignant disease. Macrophage phagocytosis was impaired through decreased mitochondrial function which could be rescued pharmacologically. MNPs inhibited the ability of macrophages to effectively present OVA-antigen preventing TCR-specific activation, an effect that could be restored by blocking PD-1/PD-L1. These findings indicate that MNPs impair macrophages via unique mechanisms linking phagocytic and bioenergetic dysfunction. Loss of antigen-presenting capabilities in MNP-laden macrophages may compromise immunosurveillance. As such, MNPs have the potential to increase susceptibility to lung disease independent of the conventional mechanisms of inflammation and oxidative stress. Clinical relevanceO_LIBioaccumulation of micro- and nanoplastics in macrophages impairs their ability to function as antigen-presenting cells increasing susceptibility to pathogenic and malignant disease. C_LIO_LIPulmonary macrophages residing in micro- and nanoplastic laden lungs possess transcriptional profiles associated with endocrine system disorders, gastrointestinal disease, and cancers. C_LI

Background: Lung cancer in never-smokers is rising, with a substantial proportion harboring the EGFR mutation. While fine particulate matter (PM2.5) is a recognized risk factor, other intervenable pollutants and built environmental factors remain unknown. Objectives: To identify urban characteristics associated with EGFR-mutant (vs. wild-type) lung cancer using high-resolution spatiotemporal data. Methods: We analyzed 2,699 lung cancer patients with documented EGFR status treated at a high-volume academic medical center in New York City. Patient residential addresses were linked to high-resolution (300m x 300m) 5-year cumulative exposures to 3 air pollutants and 26 urban features. We developed Light Gradient Boosting Machine (LightGBM) models to classify EGFR status, comparing a basic clinical model with established predictors (Asian, female, never-smoking status, and adenocarcinoma histology) to an extended model with additional urban factors. Predictive performance was assessed based on discrimination (AUC). Results: We included 2,699 patients, of whom 54.1% were female and 25.8% self-identified as Asian, 11.2% as Black, and 7.4% as Hispanic; and 29% had EGFR-mutated cancer. The extended model showed modest improvements in discrimination (AUC: 0.775 [95% CI, 0.739-0.809] vs. 0.768 [0.723-0.811]), compared to the clinical model. Newly identified factors for EGFR-mutant status included black carbon (BC), nitrogen dioxide (NO2), proximity to airports, reduced access to public transportation, elevated noise levels, and lead exposure. Conclusions: Traffic-related pollutants (BC, NO2) from diesel engines and motor vehicles, and proximity to airports, were among the novel spatiotemporal features associated with EGFR-mutant lung cancer. These results may inform policy interventions.

BackgroundCase-based infectious disease surveillance is subject to ascertainment bias when testing intensity varies across time and population subgroups. We previously developed a regression-based test adjustment methodology using Standardized Testing Ratios (STRs) to correct for differential testing patterns in COVID-19 surveillance data. Wastewater-based surveillance (WWS) measures viral burden in the community independently of diagnostic testing behavior, making it a valuable external validation tool for test-adjusted case estimates. MethodsWe analyzed 111 weeks of paired wastewater and case surveillance data from Ontario, Canada (July 19, 2020 to August 28, 2022). Wastewater SARS-CoV-2 signals from 107 sewersheds across 34 public health units were normalized within sewersheds and aggregated using population-weighted averages. We compared wastewater correlations with crude reported and test-adjusted case counts using Spearman rank correlations, linear regression, and negative binomial distributed lag nonlinear models (DLNM), stratified by epidemic period. ResultsTest-adjusted cases correlated substantially more strongly with wastewater signals than crude reported cases overall (Spearman {rho} = 0.849 vs. 0.679; linear R{superscript 2} = 0.609 vs. 0.191). The advantage of test adjustment was greatest during the Omicron wave, when population-level diagnostic testing contracted sharply following PCR eligibility restrictions ({rho} = 0.924 vs. 0.604; R{superscript 2} = 0.815 vs. 0.470). DLNM incorporating the wastewater signal explained substantially more variance in test-adjusted than crude reported cases (McFadden pseudo-R{superscript 2} 0.898 vs. 0.776), despite similar lag-response structure for both outcomes. ConclusionsWastewater surveillance provides compelling independent validation of a previously described test adjustment methodology for COVID-19 case surveillance. The agreement between wastewater signals and test-adjusted cases was strongest precisely when testing scarcity was most severe, supporting the use of test adjustment to recover accurate infection dynamics from case surveillance data during periods of changing testing access and policy.

We examined associations between a 15-component urinary biomarker mixture related to consumer product chemical exposure and wearable-derived circadian light exposure patterns in U.S. adults. Using National Health and Nutrition Examination Survey (NHANES) 2011-2014, we studied adults aged 20 years or older with valid wrist-worn ambient light data and urinary chemical biomarkers (N = 1,666). Eight circadian light metrics were derived from hour-level ActiGraph GT3X+ data. A standardized chemical burden index and quantile g-computation were used in survey-weighted linear regression adjusted for age, sex, race/ethnicity, poverty-income ratio, education, body mass index, cotinine, sleep duration, and season. Higher chemical burden was associated with greater morning light ({beta} = 0.54; 95% confidence interval [CI]: 0.14, 0.94), greater nighttime light ({beta} = 0.55; 95% CI: 0.21, 0.89), and earlier light centroid timing ({beta} = -1.37 hours; 95% CI: -2.14, -0.59) after false discovery rate (FDR) correction. Quantile g-computation confirmed these three outcomes. No sex modification was observed (all interaction P > .23). Higher consumer product chemical mixture burden co-occurred with an early-shifted circadian light exposure profile, consistent with shared behavioral, occupational, and environmental determinants.