Toxicology Mechanisms and Methods最新文献

Drug-drug interactions (DDIs) remain a major concern in medication safety. Although advanced artificial intelligence methods such as deep learning have improved DDI prediction, their adoption is limited by the need for specialized expertise and complex model development. This study introduces the first application of the AutoGluon AutoML framework to DDI prediction using molecular features, aiming to automate and simplify model development. A curated subset of 100,000 drug pairs from DrugBank was used, employing three molecular representations: 2D molecular descriptors, 2048-bit Morgan fingerprints, and their combination. Models were trained using AutoGluon-Tabular with no manual hyperparameter tuning. The descriptor-only model achieved the best performance, with 84.4% test accuracy and an AUC of 0.916, outperforming fingerprint-based and hybrid models. Feature importance analysis identified key physicochemical and topological descriptors-such as drug-likeness, electrotopological indices, and hydrophobic surface area-as critical predictors of DDIs. These results demonstrate that AutoML can extract chemically meaningful patterns while reducing technical barriers. Overall, our results validate AutoGluon as a scalable approach to DDI prediction that provides chemically meaningful, feature-level interpretability, and lay the groundwork for future applications involving larger datasets and more complex chemical representations.

We explored the complex effects of formaldehyde (FA) on lung cancer through network toxicology and molecular docking techniques, focusing on understanding the molecular mechanisms by which FA affects lung cancer from a biological network perspective. With the information of formaldehyde and lung cancer targets provided by databases (ChEMBL, STITCH, GeneCards, OMIM), we identified key potential targets that are closely related to formaldehyde and lung cancer.Protein-protein interaction(PPI) networks for core targets were constructed using the STRING database, and ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the David database. Subsequently, molecular docking simulations of key target proteins with FA were performed using AutoDock software to visualize binding interactions. Finally, utilizing the PanglaoDB database, we conducted data mining of single-cell RNA sequencing data to find cell types where a certain set of genes are expressed. The results showed that the key genes for formaldehyde effects on lung cancer were mainly concentrated in metabolism-related signaling cascades, including pyruvate metabolism, fatty acid metabolism, and Pantothenate and CoA biosynthesis pathways, and the core genes ADH5, ADH4, ADH1B, ADH6, and ADH7 were screened by PPI with GO and KEGG analysis. Subsequently, molecular docking simulations of the screened key genes with FA confirmed the robust binding interactions between formaldehyde and the core targets in the key genes (binding energies were all less than -1kcal/mol). Single-cell RNA sequencing distribution analysis showed that ADH5 and ADH1B were significantly enriched in Fibroblasts cell clusters, and ADH7 was significantly enriched in Basal cells cell clusters. Our study provides key targets and pathways for understanding the complex molecular mechanisms by which FA affects lung cancer, reveals complex relationships that are difficult to find by traditional toxicological methods, and provides insights into strategies for preventing lung cancer caused by FA exposure.

Environmental pollutants often induce morphological alterations in developing organisms, yet assessments are commonly subjective, limiting reproducibility and sensitivity. We developed and validated a semi-automated brightfield high-content imaging (HCI) pipeline to quantitatively detect morphological changes in zebrafish embryos. Using FishInspector software, we adapted image analysis for microscopy systems without automated embryo positioning, extending applicability across standard laboratory setups. To validate the approach, zebrafish embryos were exposed for 96 h to two previously characterized pollutant mixtures (PFOS + PCB126; PFOS + B[a]P + arsenate) known to cause developmental effects. The pipeline sensitively quantified phenotypes, including reduced swim bladder and shortened body length. These endpoints reflect developmental delay, highlighting the method's ability to capture mechanistically relevant effects. Such changes may reduce physiological performance and behavior, ultimately impacting fish populations. While earlier subjective scoring identified some similar alterations, our findings underscore the advantages of quantitative, semi-automated morphology assessment. The method improves reproducibility, enables standardized comparisons across studies, and increases sensitivity to detecting subtle morphological effects. By integrating brightfield imaging with semi-automated analysis, this approach broadens the toxicological toolbox for developmental hazard assessment and mixture toxicity research.

Previous studies have identified associations between lead (Pb) exposure and the incidence of Alzheimer's disease (AD), yet the underlying mechanisms are still missing. This investigation verified the association between Pb exposure burden and AD risk in a small case-control study. Using a nontargeted quantification lipidomic assay, the role of 3034 lipid metabolites in the associations between Pb exposure and AD risk was also explored. The results showed that serum Pb levels in AD patients were significantly higher than in control individuals. Meanwhile, serum Pb levels were positively associated with an increased risk of AD (OR = 1.10, 95% CI = 1.04-1.15). Lipidomic assay identified that four lipid metabolites, including phosphatidylcholine (PC) (33:2e), diacylglycerol (DG) (19:1e), sphingomyelins (SM) (d38:4), and phosphoserine (PS) (39:1), were significantly altered in the serum of AD patients. Among them, PC(33:2e) and SM(d38:4) were positively correlated with serum Pb levels. Moreover, PC(33:2e) and SM(d38:4) demonstrated mediation contributions of 60.49% and 20.38%, respectively, in the association between Pb exposure and AD incidence. Network toxicology suggests that Pb exposure may affect lipid metabolic processes in AD by modulating the activation of the MAPK, PI3K-Akt, AMPK, mTOR, and autophagy pathways. Our findings reveal novel insights into AD pathogenesis, suggesting that lipid metabolites may play a mediating role in the association between Pb exposure burden and AD risk.

Chemical pollution threatens the balance, resilience and health of coastal ecosystems, and there is a need for relevant tools to monitor and assess the sensitivity of these vital ecosystems. The common periwinkle (Littorina littorea) is a key intertidal species of high ecological and biomonitoring relevance. This study aimed to develop a rapid toxicity test to evaluate behavioral responses of L. littorea utilizing 3,4-dichloroaniline (3,4-DCA) as a model compound. The snails were exposed to five concentrations (0.4-15.9 mg/L) over a four-day period, followed by a two-day recovery period. Behavioral endpoints assessed included active suction, righting performance, and feeding response. The exposure resulted in a concentration-dependent decrease in active suction, with snails retracting into their shells, which significantly reduced their oxygen consumption, indicating avoidance behavior. Post-exposure recovery demonstrated impaired righting performance and feeding activity, where higher 3,4-DCA concentrations correlate with reduced responsiveness. Notably, even at the lowest exposure concentration, fewer than 20% of snails were able to right themselves within 24 h, underscoring this as a highly sensitive behavioral endpoint. Feeding assays using Ulva lactuca revealed dose-dependent reductions in feeding activity. In conclusion, our study illustrates that L. littorea displays sensitive and quantifiable behavioral responses to chemical exposure, thereby reinforcing its potential as a non-model species for marine ecotoxicity testing.

Diquat is used in agriculture as an herbicide but poses significant health risks upon exposure. Current treatment for toxic exposures to diquat focuses on supportive care, and there is a need for better understanding of the molecular mechanisms underlying diquat-induced injury in order to develop more targeted antidotes. To this end, TGF-alpha transgenic mouse hepatocyte (TAMH) cells were exposed to various concentrations of diquat to determine toxicologically relevant concentrations followed by subsequent transcriptomic analysis. Data mining from the MicroArray Quality Control (MAQC)-II dataset, which was accessed through the Gene Expression Omnibus (GEO) was also leveraged during the gene network analysis. A median lethal concentration (LC₅₀) for diquat in the TAMH line was determined to be 18 μM, with significant cell death observed at 9 h. Microarray data identified 3578 significantly altered transcripts in the TAMH model and 6554 from the MAQC-II dataset, with notable overlap in gene expression changes. Pathway analysis using Database for Annotation, Visualization and Integrated Discovery (DAVID) highlighted MAPK signaling as playing a role during diquat-induced toxicity in both models, with 11 shared transcripts suggesting a conserved molecular response across rodent species. This study aimed to investigate the molecular mechanisms behind diquat-induced toxicity using TAMH cells and identified MAPK signaling pathway as involved. By demonstrating the utility of combining GEO and DAVID for pathway analysis, this study not only highlights potential therapeutic targets for diquat toxicity but also presents a broadly applicable, cost-effective strategy for toxicogenomic research.

Short-chain per- and polyfluoroalkyl substances (PFAS) are increasingly being used as substitutes for long-chain PFAS due to their lower bioaccumulation potential. However, their persistence and mobility can lead to toxicity and pose significant long-term health risks. Hence, the present study aims to investigate the toxicity and the molecular mechanisms associated with cancer and reproductive toxicity linked to short-chain PFAS based on network toxicology and molecular docking. The short-chain PFAS representatives used in this study include PFBA, PFBS, PFHxA, and PFHpA. The predicted biological targets for PFBA, PFBS, PFHxA, and PFHpA are 6, 2, 20, and 34, respectively. Potential targets from the disease library were identified and analyzed for protein-protein interactions and pathway enrichment. The top five targets were selected for molecular docking studies to examine interactions. Molecular docking indicated strong interactions between biological targets and pollutants, mainly through hydrogen bonds and salt bridges. Short-chain PFAS representatives have shown strong interaction with proteins such as HDAC3 (-6.133 kcal/mol), SHBG (-6.176 kcal/mol), PPARD (-6.355 kcal/mol and -6.205 kcal/mol), and FABP4 (-6.091 kcal/mol). This study also used molecular dynamics (MD) simulations to validate interactions, revealing significant dynamic behavior between proteins and ligands. Fourteen proteins linked to short-chain PFAS were associated with cancer and reproductive toxicity, with many targets common across diseases. Notably, PFHxA and PFHpA share several target proteins, suggesting similar effects in the body. Overall, the study provides an overview of the biological targets of short-chain PFAS and their potential health impacts.

Norfluoxetine (NFLU), a metabolite of the antidepressant fluoxetine, is a known persistent endocrine-disrupting chemical (EDC) detected in aquatic environments. This study applies the Coastal Biosensor for Endocrine Disruption (C-BED) transcriptomic tool to evaluate NFLU's effects on the marine mussel Mytilus trossulus. After an experiment in which mussels were exposed to 500 ng/L NFLU for six days, gonads from both sexes were analyzed for C-BED gene expression. Significant sex-specific changes were observed in the expression of genes encoding caveolin 3 (CAV-3) serotonin receptor (SR) and membrane-bound transcription factor protease (MBTP). NFLU downregulated CAV-3, SR, and MBTP in male gonads but upregulated CAV-3 and SR in females, with the largest change being a 21-fold decrease in CAV-3 expression in males and a 14.6-fold increase in females. These findings demonstrate that C-BED biomarkers are sensitive to norfluoxetine, while revealing pronounced sex-specific differences that underscore their importance for biomonitoring and ecotoxicological risk assessment.

Nitrosamines are a broad class of chemical compounds that are generally produced when amine congeners react with nitrosating substances, occasionally with nitrites present. Tobacco smoke, processed foods, certain medications, and industrial environments are among the many places in the environment where these substances are present. Because of their strong genotoxic and mutagenic properties, N-nitroso compounds-in particular, N-nitrosamines-have sparked worries about world safety. This review emphasizes nitrosamines' chemical interactions, metabolism, carcinogenic processes, control, and risk assessment in order to aid in this knowledge. It will help researchers manage nitrosamine-induced toxicity and promote safer pharmaceutical goods, as well as molecular biologists, analytical scientists, formulation scientists, and others in the research and development industry. The review examines the function of enzymes in nitrosamine metabolism, their capacity for DNA damage and mutagenesis, and epidemiological data correlating nitrosamine exposure with stomach and esophageal malignancies.

Coffee is a widely consumed beverage that has been shown to have numerous health benefits including positive effects on neurological and psychological conditions including depression. Although positive benefits have been observed, some epidemiological studies have shown that with high consumption of caffeinated coffee, the risk of suicide increases significantly. Therefore, the aim of this study was to investigate the toxicity of key coffee constituents in in vitro neuronal models. The viability of SH-SY5Y neuroblastoma cells was evaluated after 24 h treatment with a range of concentrations (10 µM, 100 µM, and 1000 µM) of caffeine, caffeic acid (CA), chlorogenic acid (CGA), ferulic acid, pyrogallic acid (PA), and trigonelline. Furthermore, specific cell death pathways were investigated for their role in coffee constituent-induced toxicity. It was found that high concentrations (1000 μM) of CA, CGA, and PA were toxic toward undifferentiated SH-SY5Y neuroblastoma cells and caffeine, CA, CGA, and PA toward dibutyryl cyclic AMP differentiated SH-SY5Y neuroblastoma. After mechanisms were investigated cytotoxicity appeared to be due to reactive oxygen species (ROS)-induced apoptosis. This study has shown that high concentrations (1000 μM) of key constituents of coffee were toxic toward both undifferentiated and dibutyryl cyclic AMP differentiated SH-SY5Y cells.