Chem. Res. Toxicol. [JOURNAL]
Sun
200 papers
Impact of Chemical Quality on High-Throughput in Vitro Assays: A Tox21 Study.
Ngan DK, Ye L, Hsieh JH … +11 more , Xu T, Zhao J, Sakamuru S, Tao D, LeClair CA, Zhao T, Rossoshek A, Reif DM, Simeonov A, Xia M, Huang R
Chem Res Toxicol · 2026 Apr · PMID 41955412 · Full text
The Tox21 10K chemical library, an toxicology toolbox consisting of more than 8900 unique chemical entities including environmental chemicals and drugs, has undergone analytical quality control (QC) testing after storag...
The Tox21 10K chemical library, an toxicology toolbox consisting of more than 8900 unique chemical entities including environmental chemicals and drugs, has undergone analytical quality control (QC) testing after storage at room temperature for 0 and 4 months (T0 and T4). Each chemical was previously assigned a QC grade based on purity, identity, and concentration. In parallel, the Tox21 10K library has been tested across approximately 90 assays in a quantitative high-throughput screening (qHTS) format, generating >120 M data points to date. These data were used to analyze the correlation between chemical quality and bioassay activity, as well as chemical structure. The chemical characteristics of poor-quality and unstable compounds were explored to identify structural features that should be avoided. In addition, one of the high-throughput assays measuring the induction of p53 activity by small molecules was used to test the Tox21 10K compound library at T0 and T4 due to its robust performance and reproducibility. Approximately 2% of compounds in the library showed a significant change in activity in the p53 assay between T0 and T4 (active to inactive or vice versa), which also correlated with chemical stability. Here, machine learning models were constructed using bioassay data or chemical structures to predict poor-quality (low QC grades at T0) and unstable (grade drop from T0 to T4) chemicals. Chemical structure was found to be highly predictive (0.75) of chemical quality and stability, whereas bioassay data was less predictive (0.66) but still showed better than random performance. Taken together, these findings provide valuable guidance for interpreting the Tox21 assay results and informing best practices for future chemical selection and handling.
Silver Nanoparticles Induce TET-Dependent Genome-Wide DNA Hydroxymethylation Alterations in Mouse Embryonic Stem Cells via Reactive Oxygen Species Signaling.
Chen S, Yin J, Lai W … +1 more , Wang H
Chem Res Toxicol · 2026 Apr · PMID 41937374 · Publisher ↗
Exposure to silver nanoparticles (AgNPs) poses potential health risks. Epigenetic alterations are increasingly recognized as a critical mechanistic bridge between environmental stressors and adverse toxicological outcome...
Exposure to silver nanoparticles (AgNPs) poses potential health risks. Epigenetic alterations are increasingly recognized as a critical mechanistic bridge between environmental stressors and adverse toxicological outcomes. Here, we demonstrate that exposure to noncytotoxic concentrations of AgNPs induces significant genome-wide alterations in DNA hydroxymethylation in mouse embryonic stem cells, which primarily is mediated by TET dioxygenase-dependent pathways. Further investigation shows that AgNPs activate TETs through a reactive oxygen species (ROS)-dependent manner, independent of the Ag ion. Our findings provide evidence that AgNPs disrupt TET-mediated DNA demethylation and reveal a novel epigenetic mechanism by which nanoparticles perturb DNA methylation homeostasis during early embryonic development.
Landscape of Nucleic Acid Modifications Induced by Chemical Warfare Agents.
Li K, Li H, Zhang Y … +7 more , Chen J, Wu J, Xu H, Xue J, Liu Y, Guo L, Xie J
Chem Res Toxicol · 2026 Apr · PMID 41930699 · Publisher ↗
Nucleic acids are one of the key cellular targets for chemical exposure and stress responses, and nucleic acid modification induced by chemical toxicants represents a core research area in toxicology. Toxicant-induced nu...
Nucleic acids are one of the key cellular targets for chemical exposure and stress responses, and nucleic acid modification induced by chemical toxicants represents a core research area in toxicology. Toxicant-induced nucleic acid modifications are categorized into two interconnected pathways. First is the exogenous modifications arising from direct covalent or noncovalent interactions between toxicants or their reactive metabolites and nucleic acids. Second is the endogenous modifications generated secondarily through toxicant-triggered oxidative stress, lipid peroxidation, inflammation, endogenous alkylation, and epigenetic or epitranscriptomic dysregulation. Taking prototypical electrophilic agents, chemical warfare agents (CWAs), as the focal point, this review maps a comprehensive landscape of nucleic acid modification induced by CWAs, mainly including exogenous monoadducts, cross-links, and endogenous oxidative damage and regulatory modifications. We systematically elucidate the chemical reactivity, structural diversity, and toxicokinetic behaviors of key lesions, further exploring the differential roles of these lesions as exposure or effect biomarkers and their contribution to adverse biological outcomes induced by CWAs. For different CWAs, bifunctional reactions producing DNA-DNA and DNA-protein cross-links constitute the most cytotoxic lesions, and single-base adducts represent the predominant and best-characterized modifications. In this context, nucleic acid adductomics has emerged as an untargeted strategy for comprehensively profiling diverse induced lesions at the molecular level. Mass spectrometry (MS) serves as the core analytical platform for adductomics, enabling structural identification and accurate picogram-level quantification of nucleic acid adducts. Meanwhile, next-generation sequencing (NGS) achieves high-resolution localization of endogenous modifications in certain contexts, although its applicability to bulky and chemically complex lesions remains technically challenging. It is expected that the combination of MS and NGS will unlock the capability to dissect the inherent relationship between specific modification sites, gene function perturbation, and resultant toxicological effects.
Interpretable Machine Learning to Understand Wildfire Toxicity: Bridging Chemicals, Omics, and Toxicological Outcomes via Symbolic Regression with Novel Feature Scoring.
Chappel JR, Kim YH, Gilmour MI … +4 more , Baker ES, Jaspers I, Weigand TM, Rager JE
Chem Res Toxicol · 2026 Apr · PMID 41928614 · Full text
Wildfire smoke exposures are increasingly common, consisting of complex mixtures of gases and particulates known to cause diverse pulmonary health effects. While health outcomes are regularly studied, quantitative links...
Wildfire smoke exposures are increasingly common, consisting of complex mixtures of gases and particulates known to cause diverse pulmonary health effects. While health outcomes are regularly studied, quantitative links between smoke chemical composition and toxicological outcomes remain poorly defined, limiting interpretation of wildfire smoke health risks. This study explores symbolic regression (SR) as an interpretable artificial intelligence/machine learning method to generate closed-form mathematical models linking chemical exposure to biological responses relevant to wildfire smoke. Prior to application on wildfire-relevant data sets, we benchmarked three Python-based SR packages on simulated data, assessing performance across varying noise levels and operator complexities. Insights from these simulation tests, such as the importance of including necessary operators, were incorporated when applying SR to lab-generated wildland fire exposure-toxicity data. This data set included chemical characterizations of biomass smoke exposures and corresponding pulmonary responses in female CD-1 mice ( = 60). Specifically, we evaluated the ability to predict a lung injury marker using (1) targeted measures of over 80 chemicals measured in smoke (RMSE = 17.57 mg/mL) and (2) lung tissue measures of hundreds of transcripts (RMSE = 15.12 mg/mL). Resulting error metrics were comparable to Random Forest and XGBoost models. To aid model interpretation, we developed directional ensemble contribution scores (DECS), a novel feature importance scoring method that quantifies the direction and magnitude of predictor contributions across top-performing models. Expert toxicologists also contributed to model prioritization, integrating a "biologists-in-the-loop" approach. Results highlighted polycyclic aromatic hydrocarbons as drivers of lung injury and methoxyphenols as suppressors. Transcriptomic analyses highlighted a small set of genes, which have roles in metabolism, cell proliferation, immune regulation, and oncogenic processes, with MYC proto-oncogene () showing the strongest association. Overall, this study demonstrates SR and associated DECS as practical, interpretable tools for modeling environmental mixtures, such as wildfire smoke, and their toxicological effects.
Arsenic and Cadmium in Cigar Fillers: A Comparative Study within Cigar Types and with Cigarettes.
Shrestha M, Pappas RS, Gonzalez-Jimenez N … +6 more , Gray N, Watson CH, Valentín-Blasini L, Otgonsuren M, Taylor KM, Hassink M
Chem Res Toxicol · 2026 Apr · PMID 41925306 · Full text
Cigar use has increased since the early 1990s; however, there is limited research on the quantity of carcinogenic metals such as arsenic and cadmium in cigars in general and especially within each of the numerous cigar t...
Cigar use has increased since the early 1990s; however, there is limited research on the quantity of carcinogenic metals such as arsenic and cadmium in cigars in general and especially within each of the numerous cigar types. The levels of cadmium and arsenic present in the tobacco filler of 67 little cigars, 21 cigarillos, and 19 large cigars were quantitatively analyzed using "triple-quad" inductively coupled plasma mass spectrometry (ICP-MS). Median arsenic concentrations in little cigars, cigarillos (medium-sized cigars), and large cigars were 0.219, 0.224, and 0.193 μg/g, respectively. For cadmium, the median concentration in little cigars was 1.21 μg/g while both cigarillos and large cigars had median cadmium concentrations of 1.32 μg/g. Median arsenic and cadmium concentrations on a per gram basis differed significantly across cigar types (Kruskal-Wallis, both < 0.05). Pairwise Wilcoxon tests showed no difference in median arsenic concentrations between little cigars and cigarillos, and no difference in median cadmium concentrations between cigarillos and large cigars. Metal concentrations in cigar types also varied by manufacturer and marketed flavor. High arsenic concentrations did not necessarily correspond with high cadmium concentrations for specific manufacturers and marketed flavors. Cigarettes had higher median arsenic concentration than each cigar type, and median arsenic concentration differed significantly for all cigarette-cigar comparisons (all < 0.05). For cadmium, median concentrations in cigarettes and little cigars were similar ( = 0.308), whereas cigarettes had lower median cadmium concentration than cigarillos and large cigars (both < 0.05). Although in some cases the carcinogenic metal concentrations are similar between cigars and cigarettes in this study, these two tobacco product categories have many different physical characteristics and are used differently, which likely affects mainstream smoke exposure and the related health impacts of the metal content.
Effect of Cigarette Type and Smoking Behavior on Urinary Metabolite Levels of Tobacco-Associated Toxicants.
Hendriks MG, Pauwels CGGM, Conklin DJ … +7 more , Lorkiewicz P, Boots AW, Talhout R, Winkens B, Opperhuizen A, van Schooten FJ, Remels AHV
Chem Res Toxicol · 2026 Apr · PMID 41921978 · Full text
Filter ventilation in cigarettes may alter smoking behavior and impact exposure to harmful chemicals. This study examined the effect of filter ventilation on smoking topography and urinary levels of metabolites of known...
Filter ventilation in cigarettes may alter smoking behavior and impact exposure to harmful chemicals. This study examined the effect of filter ventilation on smoking topography and urinary levels of metabolites of known tobacco-associated toxicants. Twelve male daily Marlboro Red (MR) cigarette smokers (aged 26-34) participated in the study. In a controlled environment, participants smoked regular MR, Marlboro Prime (MP, a low tar, nicotine, carbon monoxide version of MR), or ventilation holes-blocked MP (MPT; where T = taped) ad libitum on separate days. Smoking topography was recorded by using the CReSSmicro device. Urine samples were collected throughout the day, and 27 metabolites of tobacco-associated toxicants (i.e., nicotine, aldehydes, xylene) were analyzed by ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Smoking different types of cigarettes throughout the day resulted in increased urinary metabolites, including those of nicotine, aldehydes, xylene, and others. No differences were observed in intraday increases in these metabolites between smoking MR and MP. However, compared with MR and MP, smoking MPT was associated with a smaller increase in urinary concentrations of cotinine and 3-hydroxycotinine. Switching from the MR to MP or to the MPT did not significantly alter the number of cigarettes smoked. However, puff count, puff duration, and total cigarette volume smoked were significantly lower when smoking MPT. Overall, our data supports existing literature that indicates that smoking high filter-ventilated cigarettes elicits equivalent toxin exposure as conventional cigarettes. Blocking ventilation holes led to lower urinary nicotine metabolite concentrations, which may be partly due to the rapidly altered smoking topography.
Toxicity, Chemistry, and Public Health Relevance of Emerging Nicotine Analog Vapes, Pods, and Pouches.
Raghu R, Sengupta M, Lin K … +3 more , Effah F, Strongin RM, Rahman I
Chem Res Toxicol · 2026 Apr · PMID 41915848 · Full text
Electronic nicotine delivery system manufacturers, such as Charlie's Holdings Inc., ECBlend, Outlaw, and NicRiver, have recently introduced nicotine analogs, such as 6-methyl nicotine, 6-MN ("Metatine"), and nicotinamide...
Electronic nicotine delivery system manufacturers, such as Charlie's Holdings Inc., ECBlend, Outlaw, and NicRiver, have recently introduced nicotine analogs, such as 6-methyl nicotine, 6-MN ("Metatine"), and nicotinamide, NA ("Nixamide," "Nixodine," or "Nixotin-free base and salt") in products to circumvent the U.S. FDA's premarket tobacco product application (PMTA) requirements. Marketed as "tobacco-free," "PMTA-exempt," or "FDA-approved," these compounds now appear in oral nicotine pouches and disposable bars/vapes from brands such as Outlaw Dip, Kumi-Six, SBX, Katchmi, and Spree Bar under proprietary labels including "NoNic6," "Metatine," or "NIC-SAFE." These products often mimic the appeal of conventional nicotine delivery systems, with extensive use of fruit, menthol, and candy-inspired flavorings. Independent testing, however, has revealed inconsistencies between labeled and actual concentrations of 6-MN, alongside the presence of undisclosed chemical additives such as "coolants" and numerous other examples. Additionally, emerging toxicological evidence indicates that 6-MN is more potent than nicotine to cause oxidative, inflammatory, and toxic responses. This includes the activation of NF-κΒ, causes epithelial permeability, and lung remodeling due to extracellular matrix (ECM) modifications. Misleading claims by industry sources include erroneous statements that imply nicotinamide interacts with nicotinic acetylcholine receptors (e.g., methylated nicotine analogs-interaction with α4β2 nicotinic acetylcholine receptors -nAChR interactions). Despite health risks, regulatory frameworks remain ambiguous, enabling companies to circumvent oversight by exploiting loopholes around synthetic analogs. There is a need for rigorous chemical and toxicological studies to evaluate the health effects of nicotine analogs, such as 6-MN and NA, and their interactions with flavorings. This review summarizes current knowledge of chemistry, pharmacology, toxicity, product landscape, flavoring profiles, and labeling practices of 6-MN- and nicotinamide-containing and nicotinamide products, highlighting the urgent need for regulatory clarity, transparent labeling, and further chemico-toxicological assessment.
Toward In Silico NAMs Analysis of Thyroid Disruption Leading to Developmental Neurotoxicity─A Collection of AOP-Anchored Computational Models.
Judzinska B, Nisterenko W, Bulawska N … +4 more , Kowalska D, Jagiello K, Sosnowska A, Puzyn T
Chem Res Toxicol · 2026 Apr · PMID 41915611 · Full text
Thyroid disruption (TD) plays a critical role in developmental neurotoxicity (DNT), given the essential functions of thyroid hormones in brain development. The identification and assessment of DNT caused by TD have becom...
Thyroid disruption (TD) plays a critical role in developmental neurotoxicity (DNT), given the essential functions of thyroid hormones in brain development. The identification and assessment of DNT caused by TD have become a significant focus in regulatory toxicology, necessitating the use of innovative approaches that are both predictive and efficient. This study provides a comprehensive examination of in silico new approach methodologies, with a particular emphasis on (quantitative) structure-activity relationship ((Q)SAR) models. Models anchored in the adverse outcome pathway framework offer mechanistic insights and predictive capabilities for assessing DNT linked to TD. By integrating knowledge of molecular initiating events and key events associated with thyroid hormone disruption, quantitative structure-activity relationships models provide a streamlined approach for predicting DNT. This systematic review identified 44 relevant studies documenting a total of 178 predictive models. The distribution of models across endpoints reveals that the most dominant endpoints are PXR (72), TTR (45), and TPO (21). A rigorous quality assessment showed that only 32 models are fully compliant with the OECD QAF (Quality Assessment Framework) criteria. This highlights the urgent need for more robust, endpoint-specific modeling tools.
Incense Aerosol-Induced Neurotoxicity Disrupts α-Synuclein Homeostasis in a Cellular Parkinson's Disease Model, Distinct from Cigarette Aerosols.
Tseng YE, Teng MC, Huang YS … +4 more , Pan CH, Chang YP, Wang CC, Fan HF
Chem Res Toxicol · 2026 Apr · PMID 41911441 · Full text
Incense burning is a widespread indoor combustion practice, yet its neurotoxic potential and impact on α-synuclein (α-Syn) proteostasis remain poorly defined. Using SH-SY5Y cells overexpressing α-Syn as a cellular Parkin...
Incense burning is a widespread indoor combustion practice, yet its neurotoxic potential and impact on α-synuclein (α-Syn) proteostasis remain poorly defined. Using SH-SY5Y cells overexpressing α-Syn as a cellular Parkinson's disease model, we exposed cells to size-fractionated incense aerosol extracts (IAE) prepared as organic-phase (OP) or water-soluble phase (WP). α-Syn overexpression augmented vulnerability to IAE, producing greater losses in viability and pronounced increases in intracellular hydrogen peroxide (HO), mitochondrial membrane potential depolarization, and engagement of programmed cell-death pathways. Live-cell fluorescence cross-correlation spectroscopy (FCCS) revealed that both OP-IAE and WP-IAE shifted α-Syn from oligomeric to monomeric states in the cytosol, indicating disruption of oligomerization equilibrium. Antioxidant intervention revealed mechanistic differences compared with other indoor air pollutants, cigarette smoke. OP-IAE-induced cytotoxicity cannot be mitigated by -acetylcysteine (NAC) or rutin, whereas WP-IAE-induced toxicity was partially attenuated, with NAC surpassing rutin. By contrast, for cigarette aerosol extracts (CAE), both OP- and WP-CAEs were robustly rescued by NAC and, to a lesser extent, rutin. Together, these results indicate that incense aerosols, particularly OP-IAE, engage reactive oxygen species (ROS)-linked mitochondrial injury and programmed cell-death pathways while uniquely driving α-Syn monomerization, while exhibiting relative resistance to classical antioxidant intervention compared with cigarette aerosols. This work points out incense smoke as a distinct indoor neurotoxicant with implications for α-Syn homeostasis and Parkinsonian risk in exposed populations.
New Mechanistic Evidence for Perfluorodecanoic Acid (PFDA) Teratogenicity via CYP26A1-Mediated Retinoic Acid Metabolism and Signaling.
Hvizdak M, Kandel SE, Lampe JN
Chem Res Toxicol · 2026 Apr · PMID 41910604 · Full text
Craniofacial abnormalities account for roughly one-third of all congenital birth defects worldwide. A growing body of evidence suggests that - and polyfluoroalkyl substances (PFAS) are teratogenic in humans and laborator...
Craniofacial abnormalities account for roughly one-third of all congenital birth defects worldwide. A growing body of evidence suggests that - and polyfluoroalkyl substances (PFAS) are teratogenic in humans and laboratory animals, causing craniofacial morphological defects. PFAS structurally resemble the natural ligands of cytochrome P450 (CYP) enzymes involved in neonatal development, including the morphogen all--retinoic acid (RA). RA regulates over 500 target genes during embryogenesis, including those related to craniofacial development. During pregnancy, circulating RA concentrations are tightly maintained at the low nanomolar level. The fetus cannot synthesize RA , nor can the fetal liver reliably clear excess morphogen entering from maternal circulation to meet physiological demands. Therefore, maternal RA homeostasis is paramount to proper fetal growth and development. In adults, members of the CYP26 family play a primary role in RA clearance, including CYP26A1. PFAS disruption of maternal hepatic RA metabolism via CYP26 may represent one pathological mechanism for the significant birth defects associated with prenatal exposure. We performed an screening of 13 prominent PFAS to measure their potential to inhibit CYP26A1 and CYP26B1 metabolism of RA. Of the PFAS tested, PFDA was the most potent inhibitor of CYP26A1, with half-maximal inhibitory concentrations of 49.5 and 51.3 μM for 4-hydroxy- and 4-oxo-retinoic acid metabolite formation, respectively. No significant inhibition of CYP26B1 was observed. PFDA additionally perturbed RA metabolism and signaling in female primary human hepatocytes following 48 h semistatic incubations. Based on our data, the RA metabolic pathway through CYP26A1 regulation is a target for prenatal PFDA exposure, likely invoking irreversible consequences for the vulnerable fetus and neonate.
Drug-Metabolizing Enzymes in Human Keratinocytes and In Vitro Detection of Cytochrome P450-Mediated Phenolic Lamotrigine Metabolite.
Deck PN, Müller M, Glässner A … +7 more , Vogel M, Steffens M, Heubach C, Fechner G, Becker K, Weindl G, Sachs B
Chem Res Toxicol · 2026 Apr · PMID 41910223 · Full text
Drug-induced hypersensitivity reactions can manifest as severe cutaneous adverse reactions, with lamotrigine (LTG) being a known elicitor in a subset of patients. While reactive metabolites are proposed to play a role, t...
Drug-induced hypersensitivity reactions can manifest as severe cutaneous adverse reactions, with lamotrigine (LTG) being a known elicitor in a subset of patients. While reactive metabolites are proposed to play a role, the contribution of skin metabolism is not well established. Here, we characterized drug-metabolizing enzymes and transporters in primary human keratinocytes and assessed the LTG metabolism in vitro. Using a combined transcriptomic and metabolomic approach, we demonstrated that primary human keratinocytes show a limited drug-metabolizing capacity. Although xenobiotic-metabolizing enzymes and drug transporters (phases I-III) were expressed at the transcript level, key hepatic cytochrome P450 enzymes (CYPs) were undetectable at both mRNA and protein levels. Following LTG incubation, low levels of LTG-N2-glucuronide were formed in keratinocytes as well as (reactive) metabolites, including a glutathione (GSH) adduct and a putative phenolic LTG derivative, in several in vitro assays. LTG-N2-sulfate formation could not be achieved under aqueous conditions. Transcriptome profiling of keratinocytes revealed no significant response to LTG, LTG-N2-oxide, or LTG+valproate, whereas interferon-γ triggered a pronounced proinflammatory gene expression signature. These findings provide new data of LTG metabolism, highlighting a novel CYP-derived phenolic pathway linked to GSH conjugation.
Solvent and Phthalate Impurities of Health Concern in Tobacco-Derived and Synthetic Nicotine.
Shin HS, Pyo H, Oh Y … +3 more , Choi KY, Vu THV, Park D
Chem Res Toxicol · 2026 Apr · PMID 41906762 · Publisher ↗
Solvents and phthalates in synthetic nicotine (SN) and tobacco-derived nicotine (TDN) were determined using gas chromatography-tandem mass spectrometry (GC-MS/MS) and GC-MS. The analysis revealed that 16 solvents were de...
Solvents and phthalates in synthetic nicotine (SN) and tobacco-derived nicotine (TDN) were determined using gas chromatography-tandem mass spectrometry (GC-MS/MS) and GC-MS. The analysis revealed that 16 solvents were detected in SN at a total concentration of 2094 mg/kg, while 14 solvents were detected in TDN at a total concentration of 1538 mg/kg. The total solvent concentration found in SN was 1.4 times higher than that in TDN and that of the SN e-liquids was 1.8 times higher than that of the TDN e-liquids. Phthalate analysis showed that the total phthalate concentration in SN was approximately 11 times higher than that in TDN and that of SN e-liquids was approximately 15 times higher than that of TDN e-liquids. This appears to reflect that SN is more susceptible to solvent and phthalate contamination. Statistical analysis results showed that benzene, dichloromethane, toluene, and o-xylene showed statistically significant correlations between nicotine and their corresponding products. Overall, these results indicate that nicotine, especially SN, contains high levels of organic solvent and phthalate residues and should not be advertised as safe and pure.
Multitask Pretraining Framework for Improving Predictivity of Machine Learning Chemical Bioactivity Models for Low-Data Endpoints.
Wichrowski NJ, Clemens-Sewall MV, Rao KK … +8 more , Richardson C, Le NQ, Koshute PT, Liu JY, Chushak Y, Coyle JP, Sterner TR, Clewell RA
Chem Res Toxicol · 2026 Apr · PMID 41887802 · Publisher ↗
Computational models are crucial for rapid hazard screening of novel chemicals when time and resources are not available for laboratory assessment. The rise of machine learning (ML) methods powering quantitative structur...
Computational models are crucial for rapid hazard screening of novel chemicals when time and resources are not available for laboratory assessment. The rise of machine learning (ML) methods powering quantitative structure-activity relationship (QSAR) models has enabled data-driven development of predictive models for health effects screening. However, these models are typically single-task, meaning that they are trained on a single toxicological endpoint and lack transferability to similar tasks, , the ability to predict chemicals' effects on related endpoints. Thus, when predictions are needed for another endpoint, a new model must be trained from scratch. Further, single-task ML models are typically trained on very large, homogeneous data sets, which are not available for most adverse outcome endpoints. Effective hazard screening would benefit from approaches that can handle multiple small, noisy data sets recording complex chemical and biological mechanisms. To that end, we trained an ML model simultaneously on multiple tasks curated from moderate-sized (∼1000 observations) ToxCast data sets. To predict novel tasks from small (∼100 observations) ToxCast data sets, we combined our pretrained multitask model with a task-specific predictor, either a random forest or a neural network. These two components comprise a novel ML pipeline that generates and uses molecular representations from our multitask model. Compared to a common ML approach using standard chemical representations, our pipeline performed statistically better on a majority of tasks, regardless of the choice of downstream predictor. The advantage of the molecular representations from our multitask model, over those from a single-task model, is that they combine information on multiple effects to provide a model of chemical space that captures generalizable information. This work contributes to efforts to improve the utility of ML QSAR methods for predicting chemicals' bioactivity on low-data toxicological endpoints.
Machine Learning-Based Quantitative Structure Activity Relationship Modeling of Repeated Dose Toxicity: A Data-Driven Approach Following Organisation for Economic Co-operation and Development Test Guidelines 407, 408, and 422 Supported by Experimental Validation.
Pore S, Szepesi Z, Roy K
Chem Res Toxicol · 2026 Apr · PMID 41880451 · Publisher ↗
In recent years, the rapid increase in the production and environmental release of synthetic organic chemicals has raised serious concerns about their potential adverse effects on human health and the environment. Repeat...
In recent years, the rapid increase in the production and environmental release of synthetic organic chemicals has raised serious concerns about their potential adverse effects on human health and the environment. Repeated exposure to such substances can lead to significant toxicological effects, underscoring the importance of early and reliable hazard assessment. However, experimental determination of repeated-dose toxicity (RDT) is costly, time-consuming, and constrained by ethical considerations. In this study, we developed various classification-based predictive models to evaluate the subchronic RDT potential of chemicals after oral exposure. We compiled data from eChemPortal and J-CHECK databases. The data set contains two study-derived effect levels: NOAEL (no observed adverse effect level) and LOAEL (lowest observed adverse effect level), for which separate models have been developed. A key strength of this data set is that all studies followed standardized OECD test guidelines (407, 408, and 422) and were conducted under good laboratory practice (GLP) conditions, ensuring regulatory relevance and high data reliability. Multiple machine learning algorithms were systematically evaluated, and the best models were selected using a multicriteria analysis based on the sum of ranking differences (SRD) technique. The final selected models achieved accuracies on the training sets ranging from 0.665 to 0.902, while the test sets showed accuracies ranging from 0.642 to 0.682. We also conducted a substructure analysis to identify the key substructures involved in the toxicity. This analysis revealed eight structural motifs, with chlorine- and amine-group-containing aromatic systems being particularly significant. The final developed models were experimentally validated using chemical substances provided by Global Product Compliance (GPC) Europe AB. Additionally, the models were applied to the Pesticides Properties DataBase (PPDB) to screen for pesticides with potential toxicity upon repeated exposure. To facilitate accessibility and regulatory application, the final models have been implemented in both a Python-based tool and a web application. this study presents predictive models as alternatives to traditional animal testing for assessing the subchronic oral repeated-dose toxicity (RDT) of chemicals. Our models demonstrate strong statistical performance, indicating their suitability for further application, as supported by experimental validation. These models could be used for preliminary hazard screening or weight-of-evidence evaluations. An additional advantage is that these models were developed using data that were tested in accordance with internationally harmonized test protocols, thereby enhancing their acceptance for regulatory decision-making.
Graph-Based Classification with GNN-Explainer for Predicting Cardiac Toxicity Associated with Multi-Ion Channel Blockers.
Agarwal D, Sharma A, Garg P
Chem Res Toxicol · 2026 Apr · PMID 41875377 · Publisher ↗
Cardiotoxicity remains a critical concern in drug development, often leading to late-stage attrition of promising compounds. While traditional assessments focus on Kv11.1 channel inhibition, the Comprehensive in Vitro Pr...
Cardiotoxicity remains a critical concern in drug development, often leading to late-stage attrition of promising compounds. While traditional assessments focus on Kv11.1 channel inhibition, the Comprehensive in Vitro Proarrhythmic Assay (CiPA) initiative emphasizes the importance of evaluating additional cardiac ion channels, notably Cav1.2 and Nav1.5. In this study, we address the limitations of existing machine learning (ML) models, which typically rely on Kv11.1-specific data, by developing a deep learning (DL) framework that integrates inhibition data across all three key ion channels. A large and diverse data set (Cardio-Tox) was curated by combining experimental data from the PubChem, CUPID, and CToxPred2 repositories, totaling 34,124 molecules for Kv11.1, 1564 for Cav1.2, and 3217 for Nav1.5. Using this data set, trained GNN models are capable of individual channel prediction. The developed CardiotoxPred method, which includes the Kv, Cav, and Nav models, achieved an average prediction accuracy of 86.7% on a test data set. In addition to robust predictive performance, GNNExplainer offers interpretable visualizations by highlighting atom- and bond-level contributions via colors. These insights support cardiac molecular severity estimation, optimization, and safety profiling. All the models are freely accessible via GitHub in a user-friendly Docker container, providing a practical tool for early-stage cardiotoxicity risk assessment in drug discovery pipelines.
Mitochondrial DNA Damage Induced by Aristolochic Acid I: Recognizing the Heart as a Target Organ.
Kwok HC, Cheng KH, Chan W
Chem Res Toxicol · 2026 Apr · PMID 41873789 · Full text
We revealed in this study that prolonged aristolochic acid I (AA-I) exposure leads to an increase in oxidative stress level, and decreases in mitochondrial DNA (mtDNA) copy numbers and ATP levels in the heart, kidneys, a...
We revealed in this study that prolonged aristolochic acid I (AA-I) exposure leads to an increase in oxidative stress level, and decreases in mitochondrial DNA (mtDNA) copy numbers and ATP levels in the heart, kidneys, and liver of exposed mice. The most significant decreases in ATP levels were observed in the heart and kidneys, both of which are high-energy-consuming organs. Additionally, high levels of AA-DNA adducts were detected in the mtDNA isolated from the kidneys. These combined observations of AA-induced mitochondrial dysfunction in key energy-consuming organs may help explain previous observations of rapidly progressive renal failure and the later onset of milder hypertension in patients with aristolochic acid nephropathy.
Reactive Metabolite Post-Translational Modifications: Linking Metabolism and Cellular Homeostasis.
Gurajala KC, Omondi RO
Chem Res Toxicol · 2026 Apr · PMID 41871369 · Publisher ↗
Post-translational modifications (PTMs) include the addition of functional chemical groups, representing a crucial biochemical process that occurs after or during the synthesis of proteins, considerably impacting protein...
Post-translational modifications (PTMs) include the addition of functional chemical groups, representing a crucial biochemical process that occurs after or during the synthesis of proteins, considerably impacting protein function, stability, localization, and interaction. In this ToxWatch, we review reactive metabolite PTMs as presented at the Fall 2025 American Chemical Society Meeting as part of the symposium entitled: Reactive Metabolite Post-Translational Modifications and Their Analysis.
Characterization of the Childhood Exposome with High-Resolution Mass Spectrometry.
Teitelbaum T, Werder E, Hsiao YC … +3 more , Liu CW, Engel S, Lu K
Chem Res Toxicol · 2026 Apr · PMID 41870482 · Publisher ↗
Exposure to chemicals is significant for adults but may have an even greater negative impact on children, who undergo rapid developmental changes and heightened physiological plasticity. To better understand how broad en...
Exposure to chemicals is significant for adults but may have an even greater negative impact on children, who undergo rapid developmental changes and heightened physiological plasticity. To better understand how broad environmental factors influence chemical exposures during childhood, we analyzed 438 urine samples from 187 children participating in the Baby Connectome Project using liquid chromatography-mass spectrometry (LC-MS) to characterize the early life exposome. We integrated the mass spectrometry data with demographic information to identify chemical features associated with average household income. We identified 85 compounds whose levels were significantly associated with household income. The most common exposure sources for these compounds included food, plants, endogenous production, animals, cosmetics, and household products. Our results demonstrate the effectiveness of high-resolution mass spectrometry for profiling the early life exposome and for examining its relationships with demographic factors, as illustrated here by household income. These findings underscore the value of high-resolution exposomics in characterizing the human exposome and revealing its connections to broad environmental influences.
Endocrine Disruptor 2,7-Dibromocarbazole Disrupts Energy Metabolism and Alters Locomotor Behavior in Juvenile Zebrafish.
Zhou W, Shi L, Yang J … +8 more , Yang Z, Cheng Z, Zhang M, Liu C, Zhao N, Ji C, Zhao M, Song Y
Chem Res Toxicol · 2026 Apr · PMID 41860213 · Publisher ↗
Polyhalogenated carbazoles (PHCZs) are emerging environmental contaminants in aquatic ecosystems. Despite their reported endocrine-disrupting potential, the adverse effects of PHCZs on aquatic organisms and their underly...
Polyhalogenated carbazoles (PHCZs) are emerging environmental contaminants in aquatic ecosystems. Despite their reported endocrine-disrupting potential, the adverse effects of PHCZs on aquatic organisms and their underlying mechanisms remain poorly understood. In this study, we employed 2,7-dibromocarbazole (2,7-DBCZ) as a representative PHCZ to evaluate its detrimental effects on zebrafish and reveal the underlying mechanisms. Exposure to 2,7-DBCZ led to inhibited locomotor activity in zebrafish larvae. Mechanistically, 2,7-DBCZ significantly elevated embryonic estrogen (E) and triiodothyronine (T) levels, disrupting the normal transcription of E-related genes. Moreover, 2,7-DBCZ disrupted energy expenditure homeostasis by affecting energy metabolism-related metabolites, particularly carbohydrates (glucose 1-phosphate and fructose 6-phosphate) and amino acids (glutamine and serine). These findings suggest that the suppression of locomotor behavior in zebrafish larvae induced by 2,7-DBCZ could be attributed to its endocrine-disrupting potential, which triggers disturbances in energy metabolism. The data provide a comprehensive understanding of the ecological risks posed by PHCZs, supporting regulatory decisions regarding these emerging contaminants.
Nanoplastics at the Placenta-Fetal Interface: Emerging Chemical Toxicology Concerns.
Puthiyavalappil R, Prabhakaran P, Haribabu J
Chem Res Toxicol · 2026 Mar · PMID 41845895 · Publisher ↗
The interaction of nanoplastics with trophoblasts can potentially disrupt fetal development. The additives associated with nanoplastics, their surface chemistry, and protein corona may lead to oxidative stress and affect...
The interaction of nanoplastics with trophoblasts can potentially disrupt fetal development. The additives associated with nanoplastics, their surface chemistry, and protein corona may lead to oxidative stress and affect the cellular functions. Detailed studies revealing a clear mechanism using an advanced placental model is essential to assess developmental toxicity and guide risk assessment.
About
- Frequency
- Sun
- Papers found
- 200
- RSS feed
- Subscribe