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Open access Aug 2026

Inhalation Bioaccessibility, Pollution Assessment, and Speciation of Heavy Metals in PM2.5RD Road Dust from Urban and Semi-Urban Areas of Pakistan

Ambient exposure to fine particulate matter (PM2.5) remains a critical global public health concern; however, the speciation and bioaccessibility mechanisms of particle-bound heavy metals within the lung environment are still insufficiently understood. In particular, the role of soluble and insoluble metal species in simulated lung fluids requires further clarification. Road dust, a major contributor to PM2.5, contains heavy metals that pose significant inhalation risks, leading to oxidative stress, DNA damage, and systemic toxicity. This study investigated the contamination characteristics, bioaccessibility, pollution level, and speciation of heavy metals in PM2.5-fractionated road dust (PM2.5RD) collected from Karachi (a megacity with >27 million inhabitants) and Shikarpur (a medium-sized city of ~0.3 million) in Pakistan. A grid-based sampling approach was applied across four functional zones (residential, school, hospital, and office), yielding 48 samples. Inhalation bioaccessibility was evaluated using artificial lysosomal fluid (ALF; pH 4.5, 37 °C, 24 h), revealing moderate bioaccessibility of Cr, As, and Pb. Pollution status was assessed using contamination factor (CF), integrated pollution index (IPI), pollution load index (PLI), and potential ecological risk index. Geochemical modeling with PHREEQC 3.0 and Visual MINTEQ 3.1 was employed to simulate metal speciation, release behavior, and mineral saturation states. Overall, this study provides mechanistic insights into speciation-driven toxicity of As, Pb, and Cr in simulated lung environments, offering a scientific basis for improved risk assessment and regulatory strategies for PM2.5-associated metal exposure.

Haseeb Tufail Moryani, Shuming Zhu, Li-Ping Wang et al. · 0 citations
Open access Aug 2026

Selenium predominance in heavy metal mixtures is associated with hyperuricemia in Chinese adults: the role of insulin resistance

Emerging studies indicate exposure to heavy metals is linked with uric acid levels and hyperuricemia risk. However, the combined effects of heavy metals and the underlying mechanisms remain poorly characterized. In this community-based cross-sectional study, plasma concentrations of 20 heavy metals and serum uric acid were measured in 1,312 adults in China. Triglyceride-glucose (TyG) index, a biomarker of insulin resistance, was also calculated. Generalized linear regression model, bayesian kernel machine regression, weighted quantile sum, and quantile G-computation were used to explore the associations between single or co-exposure to heavy metals and serum uric acid levels (SUA), as well as hyperuricemia (HUA). We also explored the mediating role of TyG in these associations. And then, benchmark dose lower bound (BMDL) of selenium (Se) was calculated using benchmark dose model. In the single pollutant model, Se was positively associated with SUA (β = 0.18, 95% CI: 0.04, 0.32) and HUA (OR = 1.51, 95% CI: 1.08, 2.11). Three multi-pollutant models all revealed positive associations between metal mixtures and SUA as well as HUA, with Se being the primary contributor. Furthermore, TyG significantly mediated the associations of Se with SUA and HUA, with the mediated proportions of 47.85% and 34.72%, respectively. BMDL of Se was 118.70–233.12 μg/d based on HUA. In conclusion, metal mixtures had positive associations with SUA and HUA. Insulin resistance might be a crucial mediated pathway between Se and outcomes. Our estimated point of departure (POD) for Se was lower than those recommended by other studies.

Jing-Fu Lai, Ya-qin Zhang, Yun-Ting Zhang et al. · 0 citations