Chemical Research in Toxicology最新文献

It is uncertain whether exposure to environmental concentrations of perfluorobutanesulfonate (PFBS) disrupts the reproductive endocrine system in amphibian tadpoles. In this study, tadpoles (Lithobates catesbeianus) in G26 stage were treated with different levels of PFBS (0, 1, 3, and 10 μg/L) for 60 days to investigate whether and how PFBS affects the reproductive endocrine system and gonadal development in tadpoles. Tadpole testes exhibited structural damage to germ cells and significantly fewer spermatogonia following PFBS exposure, but the sex ratio remained unaffected. Further, PFBS exposure downregulated transcripts of genes associated with ovarian (figla and nobox) and testicular (sox9 and dmrt1) development in tadpoles. Encoding gonadotropin hormone genes were transcriptionally upregulated in the pituitary, and serum gonadotropins (FSH and LH) were elevated. Genes related to testosterone synthesis were transcriptionally upregulated, and serum testosterone concentrations were raised. The transcription of the cyp19a1 gene, which is involved in the synthesis of estradiol (E2), was downregulated, leading to decreased levels of serum E2. Furthermore, the transcript level of the vitellogenin gene was downregulated in the liver. Thus, PFBS exposure appears to disrupt the hypothalamic-pituitary–gonadal–liver axis in tadpoles, subsequently impacting gonadal development. The findings of this study indicate that environmental concentrations of PFBS threaten the reproductive endocrine system in amphibians for the first time. This provides important insights for further investigation into the risk that PFBS poses to the stability of the amphibian population.

Benzo[a]pyrene (BaP) and nicotine exposure have been implicated in lung cancer development. This study aims to elucidate the molecular mechanisms and potential biomarkers associated with this exposure in lung cancer patients. We integrated gene expression data from The Cancer Genome Atlas lung cancer cohort and the Comparative Toxicogenomics Database to identify differentially expressed genes (DEGs) associated with BaP and nicotine exposure. Enrichment analyses, survival analyses, and immune cell infiltration analyses were conducted to interpret the biological significance of these DEGs. A risk score model and a nomogram were constructed for a prognostic evaluation. We identified 163 DEGs related to BaP and nicotine exposure in lung cancer. Enrichment analysis revealed significant biological processes and pathways, including “IL-17 signaling”, “cellular senescence”, and “p53 signaling”. From the DEGs, 34 prognostic genes were identified, with CLDN5, DNASE1L3, and GPR37 being independent prognostic factors. A risk score model based on these genes showed significant prognostic value, with high-risk patients exhibiting poorer survival outcomes. Additionally, a nomogram based on these risk scores demonstrated good predictive accuracy and clinical utility. Kaplan–Meier analyses confirmed that high expression of CLDN5 and GPR37 correlated with poor survival, while high DNASE1L3 expression indicated better survival. Single-gene enrichment analyses linked these genes to immune responses, cell adhesion, and DNA methylation. Immune cell infiltration analysis revealed significant correlations between the expression of these genes and the infiltration of various immune cell types. Our findings highlight the significant role of CLDN5, DNASE1L3, and GPR37 in lung cancer associated with BaP and nicotine exposure. The constructed risk score model and nomogram provide valuable tools for prognostication, and the identified genes offer potential targets for therapeutic intervention. Understanding the influence of toxic exposure on the tumor-immune microenvironment can guide future research and treatment strategies.

Exposure assessment of hazardous volatile organic compounds (VOCs) requires accurate quantification of internal dose when establishing limits or identifying significant differences within and among populations. Even though accurate internal dose can be directly measured in blood, it is not always practical or possible to collect a suitable blood specimen. This work studies the relationship between blood and urine levels for certain smoke biomarkers (e.g., tobacco, marijuana) measured in self-reported cigarette smokers. Urine and blood specimens were collected as matched pairs from individuals at the same time. We used our latest specimen collection and VOC analysis protocols to minimize sample collection, handling, and analysis biases. From these analyses, unmetabolized urine benzene, furan, 2,5-dimethylfuran, isobutyronitrile, and benzonitrile levels were found to trend with blood levels. In addition, we measured urine creatinine levels, which were found to be significantly associated with all blood analyte concentrations (p-value ranging from <0.0063 to <0.0001) except for isobutyronitrile (p = 0.3347). For the analytes that were associated with urine creatinine levels, the ratios of urine-to-blood concentrations were substantially higher than those predicted from the urine/blood partition coefficients (K_urine/blood), which should occur if VOCs can freely equilibrate (i.e., passive diffusion) between the blood and urine. The urine isobutyronitrile concentration, which was the only analyte that was not associated with the urine creatinine level, had a urine-to-blood ratio similar to K_urine/blood. These results suggest either that urine VOC levels for certain VOCs do not equilibrate with blood levels in the urinary tract or that there is a conversion of conjugated to free forms, increasing urine VOC levels. Nevertheless, these deviations from partition theory (e.g., Henry’s Law) are analyte-specific and require characterization to establish a relationship between blood and urine levels.

The utilization of predictive methodologies for the assessment of toxicological properties represents an alternative approach that facilitates the identification of safe compounds while concurrently reducing the financial costs associated with the process. The objective of the Tox24 Challenge was to assess the progress in computational methods for predicting the activity of chemical binding to transthyretin (TTR). In order to fulfill the requirements of this task, the data set, measured by the Environmental Protection Agency, consisted of 1512 chemical substances of diverse nature. This paper describes the model that won the Tox24 Challenge and the steps taken for its further improvement. The Transformer convolutional neural network (CNN) model achieved the best performance as a standalone solution. Meanwhile, a multitask model built on a graph CNN, trained using 11 additional acute systemic toxicity data sets with increased weighting on the TTR binding activity, showed comparable results on the blind test set. The winning solution was a consensus model consisting of two catBoost models with OEstate and Mold2 descriptor sets, as well as two transformer-based models. The improvement of this solution involved adding a fifth model based on multitask learning using the graph CNN method, which led to a reduction in RMSE on the blind test set to 20.3%. The winning model was developed using the OCHEM web platform and is available online at https://ochem.eu/article/162082.

The popularity of electronic cigarettes and vaping products has launched the outbreak of a condition affecting the respiratory system of users, known as electronic-cigarette/vaping-associated lung injury (EVALI). The build-up of vitamin E acetate (VEA), a diluent of some illicit vaping oils, in the bronchoalveolar lavage of patients with EVALI provided circumstantial evidence as a target for investigation. In this work, we provide a fundamental characterization of the interaction of VEA with lung cells and pulmonary surfactant (PS) models to explore the mechanisms by which vaping-related lung injuries may be present. We first confirm the localization and uptake of VEA in pulmonary epithelial cells. Further, as PS is vitally responsible for the biophysical functions of the lungs, we explore the effect of added VEA on three increasingly complex models of PS: dipalmitoylphosphatidylcholine (DPPC), a lipid-only synthetic PS, and the biologically derived extract Curosurf. Using high-resolution techniques of small-angle X-ray scattering, small-angle neutron scattering, neutron spin–echo spectroscopy, and neutron reflectometry, we compare the molecular-scale behaviors of these membranes to the bulk viscoelastic properties of surfactant monolayer films as studied by Langmuir monolayer techniques. While VEA does not obviously alter the structure or organization of PS membranes, a consistent softening of membrane systems─regardless of compositional complexity─provides a biophysical explanation for the respiratory distress associated with EVALI and yields a new perspective on the behavior of the PS system.

Novichok nerve agents, such as A-230, A-232, and A-234, were classified as Schedule 1 chemicals under the Chemical Weapons Convention (CWC) by the Organisation for the Prohibition of Chemical Weapons (OPCW) following poisoning incidents in 2018. As a result, the production, storage, and use of these chemicals are strictly prohibited by CWC signatory nations. The identification of biomarkers indicating Novichok exposure in humans is crucial for prompt detection and response to potential incidents involving these banned chemical weapons. In this study, BChE was isolated from human serum samples exposed to Novichok nerve agents in vitro using immunomagnetic capture, followed by enzymatic digestion with Pronase or proteinase K to generate new peptide biomarkers indicative of exposure. We identified nine previously unpublished Novichok-adducted peptides generated through enzymatic digestion with proteinase K and Pronase using liquid chromatography-high-resolution mass spectrometry. Two peptides, [Agent]-serine-alanine for proteinase K digestion and [Agent]-serine-alanine-glycine for Pronase digestion, were selected for optimization due to their abundance. The analysis was subsequently transferred to an LC-triple quadrupole system to enhance throughput and detect these new biomarkers at the limits of detection corresponding to BChE inhibition levels of 3.90% or less. These additional biomarkers can improve laboratory preparedness for OPCW-designated biomedical testing laboratories as well as other clinical and investigative laboratories tasked with responding to emergencies involving these highly toxic chemicals.

Perfluorodecanoic acid (PFDA), a C10 fluorine-containing compound, is used widely and found to be present anywhere. However, whether it has reproductive toxicity for fetal Leydig cells and the underlying mechanisms remain unknown. PFDA was investigated for its effects on fetal Leydig cells (FLCs) following exposure to 0, 1, 2.5, and 5 mg/kg/days (gavage to dams) from day 14 to day 21 during gestation. The study showed that in utero medium-dose PFDA (1, 2.5 mg/kg/days) exposure increased fetal body weight. However, PFDA markedly reduced serum testosterone levels, downregulated FLC genes (Lhcgr, Star, Cyp11a1, Hsd3b1, Cyp17a1, and Insl3), and decreased their protein levels in neonatal rat testes. PFDA at 5 mg/kg/day altered lipid metabolism with upregulation of Elovl1 and downregulation of Scd2, subsequently inducing endoplasmic reticulum stress. Additionally, PFDA exposure downregulated transcription factor Gli1, thereby inhibiting fetal Leydig cell differentiation. Meanwhile, PFDA reduced testosterone biosynthesis in R2C Leydig cells in vitro, and the endoplasmic reticulum stress inhibitor tauroursodeoxycholic acid (TUDCA) reversed this process. In conclusion, PFDA disrupts fetal rat testicular lipid metabolism, induces endoplasmic reticulum stress, and interferes with the steroidogenesis network, leading to fetal Leydig cell dysfunction. This study underscores the potential environmental risk of PFDA exposure on the development of male reproductive function development.

E-cigarette emissions, which contain a variety of hazardous compounds, contribute significantly to indoor air pollution and raise concerns about secondhand exposure to vaping byproducts. Compared to fresh vape emissions, our understanding of chemically aged products in indoor environments remains incomplete. Terpenes are commonly used as flavoring agents in e-liquids, which have the ability to react with the dominant indoor oxidant ozone (O₃) to produce reactive oxygenated byproducts and result in new particle formation. In this study, mixtures of propylene glycol (PG), vegetable glycerin (VG), and terpenes as e-liquids were injected into a 2 m³ FEP chamber to simulate the indoor aging process. 100 ppbv O₃ was introduced into the chamber and allowed to react with the fresh vape emissions for 1 h. Complementary online and offline analytical techniques were used to characterize the changes in the aerosol size distribution and chemical composition during the aging processes. We observed more ultrafine particles and a greater abundance of highly oxygenated species, such as carbonyls, in aged e-cigarette aerosols. Compared with their fresh counterparts, the aged emissions exhibited greater cytotoxic potential, which can be attributed to the formation of these highly oxygenated compounds that are not present in the fresh emissions. This work highlights the dynamic chemistry and toxicity of e-cigarette aerosols in the indoor environment as well as the indirect risks of secondhand exposure.

We have assessed the human liver microsomal (HLM) metabolism of the chemical warfare nerve agents' sarin (GB), cyclosarin (GF), and the Novichok agents A-230 and A-232. In HLM, GB showed drastically decreased stability (t_1/2 = 1.4 h). The addition of ethylenediaminetetraacetic acid (EDTA), which inhibits paraoxonase-1 (PON1), reduced the metabolism of GB in HLM suggesting at least a partial role in its metabolism (t_1/2 = 2.6 h). The absence of NADPH (a requirement for CYP activity) had a major impact on metabolism, suggesting a role of likely CYP-mediated metabolism, which was rescued with the later addition of NADPH at 4 h. GF was also metabolized readily in HLM (Control t_1/2 = 9.7 h; HLM t_1/2 = 0.5 h), and this metabolism was mitigated by the addition of EDTA (t_1/2 (fast) = 0.7 h, t_1/2 (slow) = 4.0 h), suggesting a PON1 role in the metabolism of GF. GF in HLMs also showed a reduced metabolism without NADPH, suggesting a CYP-mediated role. We have described for the first time the clearance of A-230 in HLM (t_1/2 (fast) = 0.9 h, t_1/2 (slow) = 26.5 h), with a significantly decreased stability from the control (t_1/2 = 48.3 h) and with the formation of the A-230 acid as the major metabolite. EDTA also reduced the metabolism of A-230 in HLMs (t_1/2 (fast) = 0.8 h, t_1/2 (slow) = 62 h). A-232 metabolism was also HLM-dependent (t_1/2 (fast) = 1.2 h, t_1/2 (slow) = 1190 h), although overall it was dramatically more stable in the control (t_1/2 = 2,300 h). The metabolism of A-232 in HLMs also showed some inhibition by EDTA (t_1/2 (fast) = 0.5 h, t_1/2 (slow) = 1480 h).

N-Nitrosamine compounds in pharmaceuticals are a major concern due to their carcinogenic potential. However, not all nitrosamines are strong carcinogens, and understanding the structure-activity relationships of this compound group is a major challenge. The determination of the acceptable intake limits for this compound group is determined by applying either a simple carcinogenic potency categorization approach (CPCA) or read-across analysis from simple nitrosamines where experimental data exist. However, the emergence of structurally complex nitrosamines makes quantitative models desirable. Here, we present a two-step modeling approach based on a linear discriminant analysis of a set of quantum mechanical and classical descriptors followed by a 3D-QSAR PLS regression model to predict the logTD₅₀ of nitrosamine compounds.