Toxics

Chlorinated paraffins (CPs) are persistent, bioaccumulative, and toxic. In marine environments, most studies have focused on short-chain CPs (SCCPs) in animals, while medium-and long-chain CPs (MCCPs and LCCPs) in plants have been neglected. In this study, samples collected from kelp mariculture zones in different seasons were analyzed for the CPs’ contamination characteristics and spatiotemporal distributions in seawater and contamination profiles, bioaccumulation behavior, and dietary exposure risks in kelp. In seawater, the total concentration ranges of SCCPs, MCCPs, and LCCPs were 25.44–245.75, 8.24–27.19, and not detected at 3.26 ng/L, respectively. Spatially, the CP concentrations were influenced by industrial discharge, riverine inputs, and dilution effects, and were significantly higher in nearshore water than in offshore areas (p < 0.05). The concentrations were significantly higher in February than in May, which was attributed to emissions from winter heating and reduced vessel activity during a fishing moratorium. In kelp, the total concentration ranges of SCCPs, MCCPs, and LCCPs were 5.4–210.9, 0.007–0.87, and 0.0–4.45 ng/g wet weight, respectively. Kelp exhibited significant growth-stage-dependent bioaccumulation of CPs, with higher CP concentrations and bioaccumulation factors in its tender stage (February) than during its mature stage (May). Congener analysis revealed similar composition patterns between seawater and kelp. According to a dietary risk assessment (hazard quotient < 0.01), the potential health risks associated with kelp consumption are low.

Dysregulated lipid metabolism is increasingly implicated in the pathogenesis of chronic obstructive pulmonary disease (COPD), yet the role of lipid transporters in cigarette smoke (CS)-induced chronic pulmonary inflammation remains unclear. Phosphatidylinositol transfer protein β (PITPβ) is a key regulator of phospholipid transport and phosphatidylinositol (PI) homeostasis. This study aims to investigate the expression of PITPβ in a COPD model induced by cigarette smoke extract (CSE) and lipopolysaccharide (LPS) and to elucidate whether its upregulation is regulated by the epidermal growth factor receptor/extracellular signal-regulated kinase (EGFR/ERK) signaling pathway. This study established an in vivo model through combined CS and LPS exposure and an in vitro model through combined CSE and LPS treatment. In the rat model, significant pathological changes characteristic of COPD were observed, accompanied by marked upregulation of PITPβ, tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) expression. In human alveolar epithelial A549 cells, combined CSE and LPS treatment not only upregulated PITPβ, TNF-α, and IL-6 expression but also enhanced the phosphorylation levels of EGFR and ERK. Inhibition or silencing of ERK reduces PITPβ expression and downregulates TNF-α and IL-6 levels, whereas overexpression of ERK produces the opposite effect. Silencing EGFR reduces ERK phosphorylation while simultaneously inhibiting PITPβ, TNF-α, and IL-6 expression. Furthermore, combining EGFR silencing with ERK inhibition further decreases PITPβ expression. These findings indicate that CSE combined with LPS induces PITPβ upregulation in chronic pulmonary inflammation, with the EGFR/ERK signaling pathway at least partially mediating this process. This suggests that PITPβ may serve as a potential therapeutic target for COPD.

We investigated benzene variability in an urban environment using an interpretable, setting-based artificial intelligence framework. A seven-year dataset (2017–2023) of hourly pollutant concentrations (benzene, NO₂, SO₂, CO, O₃) measured in Zagreb (Croatia) was analyzed, as were meteorological variables. Multiple-ensemble decision tree models were developed, with hyperparameters optimized using metaheuristic algorithms. The best-performing model, Extra Trees optimized by the Sine Cosine Algorithm, achieved an R² of 0.87. Model interpretation employed Shapley additive explanations (SHAP), followed by PaCMAP embedding and HDBSCAN clustering to identify coherent environmental settings. Seven settings (C0–C6) and one residual group were identified, representing pollution-enhancing, suppressing, and transitional regimes. Two settings dominated benzene extremes. C6 reflected winter stagnation, characterized by strong combustion influence (CO contribution of 11.9%), shallow boundary layers (~290 m), weak winds, and high humidity. C4 represented a synoptic stability regime with enhanced heat fluxes and diminished after the COVID-19 period, consistent with altered anthropogenic activity. Low-benzene settings (C0, C1, C3) were associated with stronger mixing and higher oxidizing capacity, while transitional settings (C2, C5) reflected moderate conditions. Overall, the results show that a small number of environmental settings governed the benzene extremes, providing a transferable and interpretable framework for air quality assessment and policy support.