Toxicological Sciences最新文献

A chronic bioassay investigating radiofrequency (RF) carcinogenicity, intentionally designed to be conducted simultaneously in Korea and Japan, using the same research protocol and experimental environment. The study aimed to assess the potential carcinogenicity of Code Division Multiple Access (CDMA)-modulated 900 MHz RF signals at a whole-body specific absorption rate (SAR) of 4 W/kg, which is the reference level of the international human safety guideline, and to verify the key findings from the National Toxicology Program (NTP) study at that SAR level. Two reverberation chamber systems were used for RF exposures, and the same study protocols were followed. Male Harlan Sprague-Dawley (Hsd: Sprague Dawley® SD®) rats were randomly assigned to cage-control, sham-exposed, or RF-exposed groups. The exposure started on gestational day 5 and lasted for 18 hours and 20 minutes each day, with 10-minute on/off cycles. The project included a 28-day toxicity study, a 2-year carcinogenicity study, and a 14-week genotoxicity test. Histopathological evaluations were conducted in a partially blinded manner. The results were independently analyzed and submitted separately based on each country's research findings. In the Korean study, no statistically significant changes in tumor incidence or survival rates were observed. No significant RF-related effects were detected in the heart, brain, or adrenal glands. No changes in body temperature. Genotoxicity tests showed no evidence of DNA damage or mutation. In conclusion, the Korean part found that long-term exposure to CDMA-modulated 900 MHz RF was neither carcinogenic nor genotoxic at a SAR of 4 W/kg in male rats.

The potential carcinogenic and genotoxic effects of radiofrequency electromagnetic fields, particularly those emitted by mobile communication systems, have raised public health concerns. A previous study by the U.S. National Toxicology Program suggested increased incidences of gliomas and cardiac schwannomas in rats exposed to high levels of RF radiation. To evaluate these findings, an international collaborative study was initiated between Japan and Korea. Male Hsd: Sprague Dawley® SD® rats were exposed to 900 MHz CDMA-modulated RF-EMFs at a whole-body specific absorption rate of 4 W/kg for 18 hours and 20 minutes daily over two years. The study included a 28-day preliminary toxicity study, genotoxicity assays (alkaline comet and micronucleus tests), and a two-year carcinogenicity assessment. All procedures followed OECD guidelines and Good Laboratory Practice. No statistically significant increases in the incidences of neoplastic or non-neoplastic lesions were found in any major organ, including the brain, heart, and adrenal glands. Genotoxicity assays revealed no evidence of DNA damage or chromosomal aberrations in RF-exposed rats. A higher survival rate in the RF-exposed group, likely due to lower body weight and food consumption, was observed. This study performed in Japan, jointly planned and executed by Japan and Korea, provides strong evidence that long-term exposure to 900 MHz RF-EMFs did not produce reproducible carcinogenic or genotoxic effects in male rats. Combined with data from the Korean counterpart study, these results are expected to contribute to future international assessments of the carcinogenic potential of electromagnetic radiation.

Nephrotoxicity is a major concern in the safety assessment of chemicals and drugs. Computational modeling, particularly the use of quantitative adverse outcome pathways (qAOPs), offers a promising strategy to improve the translation from in vitro to in vivo, thereby facilitating reliable predictions of in vivo adverse outcomes and potentially reducing the need for animal testing. Platinum-based drugs are widely used in chemotherapy, yet their clinical application is frequently constrained by nephrotoxic effects. Here, we focus on the development of ordinary differential equation (ODE)-based qAOPs for platinum-induced nephrotoxicity by defining both an in vitro and an in vivo data-driven model. The in vitro model incorporates newly generated, time-course gene expression and propidium iodide (PI) staining data from RPTEC/TERT1 cells exposed to cisplatin. The in vivo model employs published rat data, including dose-response platinum kinetics as well as single-dose time-course platinum kinetics, gene expression and histopathology data. Our quantitative approach shows that key processes in the AOP related to immune system activity are non-linear. Specifically, clearance of necrotic kidney cells by immune system activity counters damage accumulation on a timescale of days, yet low-level inflammation still cumulatively affects kidney failure in the long run. Moreover, we perform quantitative in vitro to in vivo extrapolation (QIVIVE) to link the two models. With this approach, in vivo adverse outcome predictions can be made in the future not only for platinum-based compounds but also for the safety assessment of other chemicals and drugs, reducing the need for animal testing.

Per- and Polyfluoroalkyl Substances (PFAS) are a diverse class of highly fluorinated persistent synthetic chemical pollutants. Major routes of human exposure include ingestion of contaminated drinking water and foods including dairy. Consumption of PFAS-contaminated milk and dairy is especially concerning for infants and children who are particularly sensitive and most highly exposed. Here we report findings of quantitative analysis of PFAS binding to β-lactoglobulin (β-Lg), the major whey protein in bovine milk, using differential scanning fluorimetry to determine binding affinities for 17 PFAS; except for uncharged fluorotelomer alcohols, β-Lg bound each PFAS congener tested, supporting a key role of charged functional groups in binding. The perfluoroalkyl carboxylic acid trifluoroacetic acid (TFA) bound with lowest affinity (Kd = 8.6 mM) and long chain congeners PFNA, PFDA, and PFUnDA bound with highest affinities. Evidence of significant cooperative binding was found for TFA, PFDA, PFUnDA, and PFOS. Molecular docking was used to define molecular mechanisms of PFAS binding by β-Lg and across the calycin super family of lipocalins and fatty acid binding proteins. All calycins were predicted to bind PFAS in the calyx domain with ΔG of binding ranging from -5.3 to -9.4 kcal/mol, revealing that the binding affinity for many PFAS are greater than those for binding albumin. In total, this study has identified the calycin protein superfamily as PFAS binding proteins, most of which have well-characterized functions related to key endocrine and toxicological pathways associated with the adverse consequences of PFAS exposure.

There is a critical need to understand pathophysiological mechanisms involved in injury from acute chlorine gas (Cl2) exposure. Limited information is available regarding time course and mechanisms of injury after acute Cl2 exposure due to lack of human clinical data and limited fidelity of pre-clinical animal models. We designed and integrated a Cl2 exposure platform to generate and deliver precise concentrations of Cl2 to a microfluidic human airway-on-a-chip microphysiological system in vitro model. Chemical, biological, structural and functional airway-on-a-chip responses to Cl2 exposure were characterized across multiple concentrations, exposure times and post-exposure timepoints. Transcriptomics and metabolomics analyses delineated key molecular, cellular, and physiological pathways involved in acute response to Cl2 exposure. This work represents a significant advancement towards high-throughput, human-relevant characterization of pulmonary toxicants and medical countermeasure development, addressing critical gaps in toxicology modeling while reducing reliance on animal studies.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is one of the most prevalent liver disorders, affecting approximately one-third of the global adult population. The disease begins with hepatic fat accumulation (steatosis) and can progress to inflammation, fibrosis, and hepatocellular carcinoma. To elucidate the complex mechanisms underlying MASLD, we have developed a novel mathematical model that integrates glucose and lipid metabolism, oxidative stress, insulin signaling and resistance, and cytokine function. We demonstrated that variations in extracellular fatty acid and lactate concentrations, as well as alterations in the activities of important glycolytic and triglyceride-synthesizing enzymes observed in actual patients, exert a substantial impact on oxidative stress and subsequent cellular damage. Moreover, this model enabled us to evaluate daily metabolic dynamics characteristic of steatotic liver-specific protein patterns. Importantly, it also allowed simulation of cytokine release from hepatocytes into the blood circulation (autocrine and endocrine effects) and the impact of locally elevated cytokine concentrations derived from immune cells (paracrine effects). Our model revealed the dynamics of the early stages of MASLD progression in response to alterations in blood metabolites levels, hepatic enzyme activities, insulin profiles, and cytokine patterns. Furthermore, we identified specific combinations of these factors that may alleviate the hepatic fat accumulation or oxidative stress, highlighting the importance of patient specificity. This study presents the first mechanistic framework constructed based on experimental data to describe the crosstalk among hepatic metabolism, insulin, and cytokines, serving as a powerful tool for elucidating disease mechanisms and developing therapeutic strategies.

Why and how does cancer start? Building from a Symposium at the 2025 Society of Toxicology meeting, we convened a group of international experts to answer this seemingly simple question. As experimental evidence has evolved, perspectives on cancers' origins have shifted from the accumulation of DNA mutations in single cells to complex processes involving signals from an altered tissue microenvironment which promote tumorigenesis. Carcinogen exposures impact the biology of the microenvironment in complex and tissue-specific ways. These changes can include the infiltration of inflammatory cells that produce growth factors, neo-angiogenesis, morphological changes, and immune tolerance that avoids immune-mediated elimination. In this in-depth review, we discuss the evidence linking chemical-driven microenvironmental changes in the development of a range of solid and liquid tumors. We discuss specific phenotypic alterations, such as selection pressure driving clonal expansion and cellular plasticity and reacquisition of stem cell states, linked to carcinogen-induced changes in the microenvironment. We describe assays and biomarkers which can allow us to experimentally assess links between chemical exposures, the microenvironment, and cancer phenotypes. We end by discussing how understanding the role of the microenvironment and malignancy in toxicology is essential for accurate cancer hazard evaluation, development of next-generation risk assessment frameworks, identifying new strategies for cancer prevention, and improving patient care.

Cardiovascular-Kidney-Metabolic (CKM) syndrome imposes a rising global health burden, yet the link between environmental metal mixtures and CKM progression remains unclear. To assess the joint effects of metal mixtures on CKM syndrome staging and identify critical toxic drivers through advanced mixture analysis. NHANES data (2011-2016) from 1,816 participants were analyzed via Weighted Quantile Sum (WQS) regression, generalized linear models (GLMs), ridge regression, Shapley Additive exPlanations (SHAP) analysis, and polynomial regression. An Adverse Outcome Pathway (AOP) framework was utilized to characterize the mechanisms of metal-mediated CKM. The WQS model revealed an association between mixed metal exposure and CKM (β = 0.502, p = 0.013). Subsequently, GLMs and ridge regression further identified the associative characteristics of individual metals, with all three models pointing to cobalt as the key driver. The SHAP model validated cobalt's dominant contribution from the perspective of marginal feature importance. Additionally, a polynomial equation analysis showed that cobalt exhibited a linear dose-response relationship with CKM syndrome. Based on these findings, the AOP framework furtherly identified that early CKM stages are linked with cobalt-related metabolic and immune dysregulation. In contrast, late stages involve disruptions in calcium homeostasis, lipid metabolism, and cell apoptosis-survival balance. Our findings highlight the impact of metal exposure on the progression of CKM syndrome, the AOP framework has deciphered stage-specific mechanisms of cobalt, revealing distinct toxicological pathways in early versus late CKM.

New approach methods (NAMs), including in vitro paradigms, are needed to increase throughput, sustainability, and ethicality in toxicity research. However, selecting optimal cell culture models that mimic in vivo physiological conditions is challenging. To identify cell lines that best recapitulate physiological cells, we compared gene expression signatures of cell lines and in vivo tissues. We curated 214 transcriptomics datasets from 17 human and mouse hepatic cell lines representing hepatocytes, hepatic stellate cells, and cholangiocytes and determined basal gene expression profiles for each. We also collected 7 in vivo single cell RNA sequencing (scRNAseq) datasets from human and mouse livers, which provide physiologically relevant transcriptome profiles for hepatic cell types. We compared cell line transcriptome profiles to liver scRNAseq data to determine which cell lines best represent in vivo physiology for each cell type and compared genes, regulatory networks, and biological pathways between cell lines and hepatic cell types. We further analyzed 15 cell line, in vivo, and primary hepatocyte datasets from hepatotoxicity studies to relate baseline patterns to toxicological responses. We identified HepaRG as optimal to model hepatocytes both at baseline and in hepatotoxicity application studies of diverse toxicants, and further provided biological insights into the key differences of some of the widely used hepatic cell lines from in vivo biology. Overall, we present a new in silico approach that leverages existing big data to guide selection of cell lines with better functional relevance, which can be applied to in vitro modeling of other tissues and broad biomedical applications.