Aug 2026· Environmental Pollution· pp.
128961
· 0 citations· 45 references
Medicine
Abstract
Air pollution, particularly particulate matter (PM), is a major driver of global morbidity and mortality, with increasing evidence linking it to neurological disorders. This study investigates the chemical composition and neurotoxic potential of PM collected simultaneously in three sites in Catalonia (Spain): Bellver de Cerdanya (rural background), Manlleu (suburban), and Mollet del Vallès (suburban-industrial). Fifty-four filter samples collected in 2022 were analyzed by GC-MS for 30 organic molecular tracers, including polycyclic aromatic hydrocarbons (PAHs) and levoglucosan. Extracts were tested in SH-SY5Y human neuroblastoma cells across six toxicity endpoints: cell viability, reactive oxygen species (ROS), acetylcholinesterase (AChE) activity, antioxidant response, xenobiotic response, and p53 activation (DNA damage response). Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) on the combined chemical-biological dataset resolved four components: a winter biomass burning component enriched in levoglucosan, dehydroabietic acid, and PAHs, inducing strong cytotoxicity, oxidative stress, and xenobiotic responses; a traffic component present throughout the year; a spring-summer secondary organic aerosol (SOA) component associated with selective AChE inhibition without cytotoxicity; and a summer primary organic aerosol (POA) component. Partial Least Squares (PLS) regression linked PM10 composition with toxicity responses. Five of six models were statistically significant (R2CV = 0.53-0.75), with the highest performance for ROS, p53 activation, and cell death (R2CV ≥ 0.62). Biomass burning markers and PAHs were the main predictors of oxidative stress and cytotoxicity, whereas biogenic SOA tracers showed low importance. These findings link specific PM10 sources to distinct neurotoxic effects and highlight the importance of controlling winter emissions.
Ambient fine particulate matter (PM2.5) is a chemically complex mixture whose health impacts are not fully captured by particle mass. Here, we developed an interpretable chemotranscriptomic framework to attribute PM2.5-induced molecular perturbations to toxicity-relevant components. PM2.5 collected from urban roadside and coastal environments was separated into whole, extractable, and unextractable fractions, characterized by LC/GC × GC-HRMS-based nontarget analysis and inductively coupled plasma mass spectrometry (ICP-MS), and evaluated using cytotoxicity testing and transcriptomic profiling in human bronchial epithelial cells. Urban PM2.5 exhibited greater cytotoxic potency per unit mass than coastal PM2.5, with extractable fractions accounting for most cytotoxic and pathway-level responses. Transcriptomics revealed distinct site-specific modes of action: urban PM2.5 preferentially induced oxidative stress, xenobiotic metabolism, and cell cycle suppression, consistent with acute, nonapoptotic injury, whereas coastal PM2.5 elicited weaker cytotoxicity but stronger interferon-mediated immune and apoptosis-related signaling. Integrating chemical abundance with pathway activity using random forest regression, SHAP interpretation, and mechanistic corroboration reduced 5,033 detected features to 444 pathway-linked candidate drivers. Fewer than 5% of features explained ∼95% of cumulative model contribution. Standard-confirmed contributors included plasticizer-related compounds, aromatic and heteroaromatic combustion products, and copper for urban PM2.5 and secondary/aged organics and nickel for coastal PM2.5. These findings support mechanism-informed prioritization of hazardous PM2.5 components beyond mass-based assessment.
Shihao Wang, Xinyu Li, Yong Han et al.· Environmental Science and Te...· 0 citations
ABSTRACT Quinalphos pesticide (QP) exposure can lead to various human health effects, including anaemia, leucocytosis with neutrophilia, hepatic damage and oxidative stress. Acute poisoning symptoms include weakness, sweating, impaired vision and neurological distress. Additionally, neurological and reproductive abnormalities have been reported in specific exposure scenarios. This study identified 16 differentially expressed genes from clinical exposure research. Integrating omics data using network biology approaches has shown that QP significantly alters the expression of 16 genes predicted to be regulated by 26 transcription factors and 41 miRNAs. The molecular docking predicted AR, ESR1, NR1I2, ESR2, CYP19A1 and JUN to have the highest binding affinity with QP. Gene ontology analysis of the DEGs revealed enrichment in pathways related to genital development, oestrogen receptor signalling, prostate gland development and response to vitamin A. The three most influential pathways by these DEGs are detected with significant enrichment in diseases, and they are linked to Cytochrome P450, arranged by substrate type, nuclear receptor transcription pathway and SUMOylation of intracellular receptors. The analysis identified 1445 drugs for 15 genes for potential drug repurposing. The network was pruned by applying the threshold value 0.1 STITCH database and score value 0.1 of the DGIdb database, resulting in the identification of 446 drug (approved and non‐approved) therapeutic targets. This analysis provides a comprehensive understanding of the mechanisms of QP‐induced toxicity, focusing on humans, and underscores the need for further studies on exposure to QP, providing valuable insights for toxicological risk assessment and regulatory evaluation.
J. Choudhari, B. P. Sahariah, Anandkumar Jayapal et al.· IET Systems Biology· 0 citations
BACKGROUND
The association between organochlorine pesticides (OCPs)/synthetic pyrethroids (SPs) and thyroid cancer (TC) remains poorly understood, with metabolic mechanisms unexplored.
METHODS
We conducted a 1:1 age- and sex-matched case-control study (n = 668). Serum levels of 27 target analytes (19 OCPs and 8 SPs) were quantified; subsequent analyses were restricted to 13 compounds (10 OCPs and 3 SPs) with detection frequencies ≥85%. Eight machine learning (ML) algorithms with Shapley Additive Explanations (SHAP) were used to identify key pollutants in the 334 case-control pairs. Untargeted metabolomics was performed in a subset of 50 age- and sex-matched case-control pairs. Mixture effects were assessed by Bayesian kernel machine regression (BKMR) and weighted quantile sum (WQS) regression. Furthermore, the Latent Unknown Clustering Integrating Multi-Omics Data (LUCID) model was employed to integrate exposure and metabolic data, enabling the identification of TC patient subgroups and the exploration of underlying metabolic mechanisms.
RESULTS
Participants (mean age 45.2 years, 82.3% female) had serum OCPs at 0.007-0.333 ng/mL and SPs at 0.046-0.095 ng/mL. ML algorithms identified fenpropathrin, β-BHC, cyhalothrin, α-BHC, and p,p'-DDD as the top five contributors to TC. Elevated OCPs/SPs exposure was significantly associated with increased TC risk (WQS: adjusted OR = 1.45, 95%CI = 1.34-2.24, P = 0.019; LUCID: OR = 9.33). Fenpropathrin was the primary contributor (BKMR posterior inclusion probability = 1.00; WQS weight = 67.6%). A total of 45 significant differential metabolites (DMs) were identified (VIP ≥1, P < 0.05, and qualitative level 1). LUCID revealed a distinct TC cluster characterized by upregulated S-sulfo-L-cysteine/adenosine and downregulated 2-hydroxycaprylic acid.
CONCLUSION
OCPs/SPs mixtures, driven by fenpropathrin, disrupt amino acid/nucleotide metabolism while suppressing organic acid metabolism, representing a potential TC-associated metabolic signature.
Fei Wang, Chunxiang Li, Linfang Zou et al.· Environment International· 0 citations
In rapidly expanding African cities, the ecotoxicological relevance of PM10 remains largely unresolved, especially where particle mass, chemical composition and emission sources are rarely assessed together. Here, 116 daily PM10 samples collected in Luanda between 27 June and 5 November 2023 were tested using the Microtox® Aliivibrio fischeri assay on aqueous extracts. Chemical speciation was combined with centred log-ratio (CLR) compositional clustering to identify recurring chemical regimes, while Positive Matrix Factorisation (PMF) was used to resolve the corresponding emission sources. Toxicity was moderate but highly variable: Toxic units after 15 min (TU15) ranged from 0.84 to 8.54, with changes in toxicity units between 5 and 15 min (ΔTU) varying from −1.51 to +4.84. Only 3 of the 116 samples showed TU15 < 1, and none reached TU15 ≥ 10. The strongest responses occurred under a metal-enriched chemical regime (C2), characterised by elevated Zn, Pb and Cd concentrations, which showed the highest mean TU15 (4.22) and ΔTU (1.52). This regime coincided with PMF evidence identifying non-ferrous metallurgy plus galvanised/metal scrap handling and burning as the factor most strongly associated with toxicity (ρTU15 = 0.63; ρΔTU = 0.78), followed by a Ni-rich metallurgical factor with possible aviation influence (ρTU15 = 0.51). Conversely, a marine/ionic chemical regime (C3) showed lower, stable toxicity, consistent with negative marine aerosol associations. These findings show that integrating chemical regimes with PMF-resolved sources identifies metal-related emissions as the main drivers of PM10 ecotoxicity.
Alan Victor da Silva, E. Vicente, Ana M. Sánchez de la Campa et al.· Toxics· 0 citations
Long-term population-level exposure data of persistent organic pollutants (POPs) are fragmented, and chemical control strategies are often based on exposure level, with limited consideration of biological relevance. Here, we reconstructed long-term exposure trajectories of 91 POP mixtures using NHANES biomonitoring data by integrating low-rank matrix completion and multitask temporal forecasting (R2 = 0.93), covering DIOXINs, organochlorine pesticides (OCPs), perfluoroalkyl and polyfluoroalkyl substances (PFASs), polybrominated diphenyl ethers (PBDEs), polychlorinated biphenyls (PCBs). Reconstructed exposure profiles were further embedded into multilayer biological networks of "exposure-biology-disease" framework focusing on neurodevelopmental disorders (NDDs, 349 subtypes) as an application scenario. Across POP categories, reconstructed population-level concentrations declined substantially (>80-95% projected by 2030-2040), which increasingly concentrated among a limited number of persistent and biologically connected chemicals. Chemical risk rankings exhibited pronounced temporal reorganization, with early period relevance largely driven by PFASs, while under low-exposure futures, disease relevance shifted toward other POP categories, particularly in protein-centric interaction networks. By integrating long-term exposure reconstruction with network-informed NDDs relevance, our study provides a dynamic framework for prioritizing control of POP mixtures. In the early postregulation period (2004-2009), PFAS dominated NDD relevance in both frameworks, accounting for more than half of the total score. By 2025, however, the relative contribution of PFAS decreased, while PBDEs and PCBs increased markedly. In sum, we proposed that given the dramatic decline of conventional POPs following the implementation of the Stockholm Convention, increasing attention should now be directed toward other emerging pollutants.
Yuanchen Chen, Gege Liu, Shuo Yang et al.· Environmental Science and Te...· 0 citations
Despite ubiquity of contaminants of emerging concern (CECs), biological consequences of combined exposure remain poorly understood, particularly regarding oxidative stress and related redox-sensitive molecular responses. We quantified 64 urinary CECs across seven chemical classes (bisphenol analogues, parabens, synthetic phenolic antioxidants, antimicrobials, organophosphate esters, neonicotinoids, and ultraviolet filters) and two oxidative stress biomarkers [8-hydroxydeoxyguanosine (8-OHdG) and 8-isoprostaglandin F2α (8-isoPGF2α)] in 142 Chinese adults. Single-chemical associations were assessed using generalized linear models, while joint associations were evaluated by elastic net regression and quantile g-computation. By integrating leukocyte mRNA sequencing profiles, we identified redox-related transcriptional signatures linking CEC exposure to oxidative stress. Fourteen and 13 CECs were associated with elevated 8-OHdG and 8-isoPGF2α, respectively. Mixture analyses showed positive associations of combined CEC exposure with both biomarkers. Key contributors in mixture models included octabenzone, bisphenol A, tris(2-chloroisopropyl) phosphate, and acetamiprid for 8-OHdG and octabenzone, triisobutyl phosphate, and 2,6-di-tert-butyl-4-hydroxy-4-methylcyclohexa-2,5-dien-1-one for 8-isoPGF2α. Transcriptomic integration indicated mixture-associated oxidative stress was accompanied by coordinated redox-sensitive gene expression changes, with shared enrichment of inflammatory and stress-response pathways (including Toll-like receptor and MAPK signaling) across chemical classes. Notably, SYT1 and CCNP emerged as recurrent transcriptomic candidates linking CEC exposure with oxidative stress, supporting coordinated transcriptional response under real-world CEC coexposure.
