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Toxics

Toxics is an international, peer-reviewed, open access journal on all aspects of the toxic chemicals and materials, published monthly online by MDPI.

Indexed in PubMed | Quartile Ranking JCR - Q1 (Toxicology)

All Articles (4,469)

Molecular toxicity prediction plays a crucial role in drug screening and environmental health risk assessment. Traditional toxicity prediction models primarily rely on molecular fingerprints and other structural features, while neglecting the complex biological mechanisms underlying compound toxicity, resulting in limited predictive accuracy, poor interpretability, and reduced generalizability. To address this challenge, this study proposes a novel molecular toxicity prediction framework that integrates knowledge graphs with Graph Neural Networks (GNNs). Specifically, we constructed a heterogeneous toxicological knowledge graph (ToxKG) based on ComptoxAI. ToxKG incorporates data from authoritative databases such as PubChem, Reactome, and ChEMBL, and covers multiple entities and relationships including chemicals, genes, signaling pathways, and bioassays. We then systematically evaluated six representative GNN models (GCN, GAT, R-GCN, HRAN, HGT, and GPS) on the Tox21 dataset. Experimental results demonstrate that heterogeneous graph models enriched with ToxKG information significantly outperform traditional models relying solely on structural features across multiple metrics including AUC, F1-score, ACC, and balanced accuracy (BAC). Notably, the GPS model achieved the highest AUC value (0.956) for key receptor tasks such as NR-AR, highlighting the critical role of biological mechanism information and heterogeneous graph structures in toxicity prediction. This study provides a promising pathway toward the development of interpretable and efficient intelligent models for toxicological risk assessment.

5 November 2025

Statistical distribution of valid data, toxic compounds, and non-toxic compounds across 12 receptors in the Tox21 dataset.

Mining and smelting release potentially toxic elements (PTEs) that threaten ecosystems and public health. However, comprehensive risk assessments of PTEs across environmental media near mining areas remain scarce. The Laoguan River Basin is located in southwestern Henan Province, China. It lies within the water source area of China’s South-to-North Water Diversion Middle Route Project. This area has high geographic and ecological importance. In this study, we analyzed the pollution characteristics of PTEs in the water–soil–crop system. We also performed a source-oriented health risk assessment by integrating Monte Carlo simulation with source apportionment. According to this study, Mo and Sb were the predominant contaminants in soils and water. Pb, Cr, and Ni were elevated in crops. The health risk assessment indicated that PTEs in surface water were at acceptable levels. In contrast, PTEs in soils pose both non-carcinogenic and carcinogenic risks, particularly to children. The estimated risks were 1% (non-carcinogenic) and 64% (carcinogenic), with ingestion as the primary exposure pathway. Source apportionment showed that the surface water pollution was mainly linked to diverse mining activities. Soil pollution was jointly influenced by the geological background and mining and agricultural activities. Crop pollution was primarily associated with mining and agricultural activities. Geological background and mining were the main driving factors of the increased health risks for children. They accounted for 83% of the non-carcinogenic risk and 79% of the carcinogenic risk. Overall, these results are crucial for pollution control, safeguarding public health and safety, and promoting balanced economic and ecological development.

4 November 2025

Location of the study area: (a) administrative divisions in China; (b) water source areas of China’s South-to-North Water Diversion Middle Route Project; (c) the study area. The red circles indicate the mining areas. The red five-pointed star indicates Beijing, China.

In this study, mulberry tree stems were used as raw material to prepare magnetic modified biochar, Fe-BC-500, using the co-precipitation method. The structure of Fe-BC-500 was systematically characterized and tested for arsenic (As) adsorption in batch experiments by varying parameters such as solution pH (3–11), the concentrations of co-existing anions (2–20 mg/L), and ionic strength (0–0.5 mol/L NaNO3). The results indicate that Fe-BC-500 exhibited optimal adsorption capacity at pH 4 and an initial As(V) concentration of 20 mg/L. The influence of co-existing anions on As(V) adsorption followed the order PO43− > SO42− > NO3. Kinetic analysis showed that adsorption of Fe-BC-500 on As(V) followed a pseudo-second-order kinetic model, with a correlation coefficient of 1.00, indicating chemical adsorption. The Langmuir model accurately described the isothermal adsorption results, indicating monolayer adsorption. Mechanistic analysis showed that As(V) was fixed on the Fe-BC-500 surface through complexation reactions, demonstrating adsorption specificity. This study provides a theoretical basis and highlights the application potential of magnetically modified biochar for removing As(V) from water.

4 November 2025

Effect of pH on As(V) adsorption onto Fe-BC-500.
  • Feature Paper
  • Review
  • Open Access

With the widespread use of emerging contaminants such as melamine (MEL) and organophosphate esters (OPEs) as alternatives to traditional flame retardants, their ubiquitous presence in the environment has raised concerns about human internal exposure and health risks. Urine, as a critical matrix for biomonitoring, enables accurate assessment of internal exposure to these contaminants and their metabolites. This review systematically summarizes the research progress on urinary biomonitoring of MEL and its derivatives (cyanuric acid (CYA), ammeline (AMN), ammelide (AMD)) and OPE metabolites. It covers analytical methods (sample pretreatment including enzymatic hydrolysis and extraction, instrumental detection via HPLC-MS/MS/UPLC-MS/MS, and method validation), exposure characteristics (global spatial differences, population disparities among sensitive groups like children and e-waste workers, and temporal variations such as postprandial peaks), and health risk assessments. Results show that MEL and CYA are widely detected in urine (detection rates > 97%), with CYA dominating total MEL (66.2–80%); OPE metabolites exhibit regional compositional differences, e.g., bis(2-chloroethyl) phosphate (BCEP) in Shenzhen and diphenyl phosphate (DPHP) in New York. Current exposure levels are generally safe, but 2–12% of sensitive individuals face potential risks. This review highlights key challenges (method standardization, limited hydroxylated OPE standards) and provides directions for future research to establish a comprehensive exposure–health risk evaluation system.

4 November 2025

Concentration levels of MEL and its derivatives in published studies [27,37,47,57,58,59,62].

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Editors: Qi Wang, Youbo Zhang, An Zhu
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Toxics - ISSN 2305-6304Creative Common CC BY license