Predicting lung dosimetry of inhaled particleborne benzo[a]pyrene using physiologically based pharmacokinetic modeling

Nano- and microplastic PBK modeling in the context of human exposure and risk assessment

Insufficient data on nano- and microplastics (NMP) hinder robust evaluation of their potential health risks. Methodological disparities and the absence of established toxicity thresholds impede the comparability and practical application of research findings. The diverse attributes of NMP, such as variations in sizes, shapes, and compositions, complicate human health risk assessment. Although probability density functions (PDFs) show promise in capturing this diversity, their integration into risk assessment frameworks is limited. Physiologically based kinetic (PBK) models offer a potential solution to bridge the gap between external exposure and internal dosimetry for risk evaluation. However, the heterogeneity of NMP poses challenges for accurate biodistribution modeling. A literature review, encompassing both experimental and modeling studies, was conducted to examine biodistribution studies of monodisperse micro- and nanoparticles. The literature search in PubMed and Scopus databases yielded 39 studies that met the inclusion criteria. Evaluation criteria were adapted from previous Quality Assurance and Quality Control (QA-QC) studies, best practice guidelines from WHO (2010), OECD guidance (2021), and additional criteria specific to NMP risk assessment. Subsequently, a conceptual framework for a comprehensive NMP-PBK model was developed, addressing the multidimensionality of NMP particles. Parameters for an NMP-PBK model are presented. QA-QC evaluations revealed that most experimental studies scored relatively well (>0) in particle characterizations and environmental settings but fell short in criteria application for biodistribution modeling. The evaluation of modeling studies revealed that information regarding the model type and allometric scaling requires improvement. Three potential applications of PDFs in PBK modeling of NMP are identified: capturing the multidimensionality of the NMP continuum, quantifying the probabilistic definition of external exposure, and calculating the bio-accessibility fraction of NMP in the human body. A framework for an NMP-PBK model is proposed, integrating PDFs to enhance the assessment of NMP's impact on human health.

Dynamic changes of DNA methylation induced by benzo(a)pyrene in cancer

Benzo(a)pyrene (BaP), the earliest and most significant carcinogen among polycyclic aromatic hydrocarbons (PAHs), has been found in foods, tobacco smoke, and automobiles exhaust, etc. Exposure to BaP induced DNA damage directly, or oxidative stress-related damage, resulting in cell apoptosis and carcinogenesis in human respiratory system, digestive system, reproductive system, etc. Moreover, BaP triggered genome-wide epigenetic alterations by methylation, which might cause disturbances in regulation of gene expression, and thereby induced cancer. It has been proved that BaP reduced genome-wide DNA methylation, and activated proto-oncogene by hypomethylation in the promoter region, but silenced tumor suppressor genes by promoter hypermethylation, resulting in cancer initiation and progression. Here we summarized the changes in DNA methylation in BaP exposure, and revealed the methylation of DNA plays a role in cancer development.

Phosphorylation of p53 by Cdk5 contributes to benzo[a]pyrene-induced neuronal apoptosis

Benzo[a]pyrene (B[a]P) is a ubiquitous carcinogenic pollutant in the environment, however, the potential neurotoxic effects of B[a]P has not been elucidated clearly. In the present study, we explored the potential involvement of p53 phosphorylation by Cdk5 in B[a]P-induced neuronal apoptosis at both in vitro and in vivo settings. For in vitro studies, primary cortical neurons isolated from the brains of Sprague Dawley (SD) rat pup were exposed to 0, 10, 20, and 40 μM of B[a]P for 12, 24, or 48 h. For in vivo studies, SD rats were injected intraperitoneally with 0, 1.0, 2.5, and 6.25 mg/kg of B[a]P every other day for 1, 2, or 3 months. Our results demonstrated that exposure to B[a]P caused a dose- and a time-dependent increase in neuronal apoptotic ratio in both in vitro and in vivo studies. There was also a dose- and a time-dependent upregulation of p35, p25, Cdk5, and phosphorylated p53 at Ser15 after B[a]P exposure. In order to explore whether B[a]P-induced increased neuronal apoptosis was through Cdk5/p53 pathway, roscovitine, a specific Cdk5 inhibitor, was applied to pretreat neurons prior to B[a]P exposure. The results showed that pretreatment of neurons with roscovitine partially rescued cells from B[a]P-induced apoptosis, and alleviated B[a]P-induced upregulation of phosphorylated p53 at Ser15. Our results suggest that Cdk5/p53 signaling pathway may be involved in B[a]P-induced neuronal apoptosis, which will provide information to further elucidate the molecular mechanisms of B[a]P-induced neurotoxicity.

Predicting the in vivo developmental toxicity of benzo[a]pyrene (BaP) in rats by an in vitro-in silico approach

Developmental toxicity testing is an animal-intensive endpoints in toxicity testing and calls for animal-free alternatives. Previous studies showed the applicability of an in vitro–in silico approach for predicting developmental toxicity of a range of compounds, based on data from the mouse embryonic stem cell test (EST) combined with physiologically based kinetic (PBK) modelling facilitated reverse dosimetry. In the current study, the use of this approach for predicting developmental toxicity of polycyclic aromatic hydrocarbons (PAHs) was evaluated, using benzo[a]pyrene (BaP) as a model compound. A rat PBK model of BaP was developed to simulate the kinetics of its main metabolite 3-hydroxybenzo[a]pyrene (3-OHBaP), shown previously to be responsible for the developmental toxicity of BaP. Comparison to in vivo kinetic data showed that the model adequately predicted BaP and 3-OHBaP blood concentrations in the rat. Using this PBK model and reverse dosimetry, a concentration–response curve for 3-OHBaP obtained in the EST was translated into an in vivo dose–response curve for developmental toxicity of BaP in rats upon single or repeated dose exposure. The predicted half maximal effect doses (ED₅₀) amounted to 67 and 45 mg/kg bw being comparable to the ED₅₀ derived from the in vivo dose–response data reported for BaP in the literature, of 29 mg/kg bw. The present study provides a proof of principle of applying this in vitro–in silico approach for evaluating developmental toxicity of BaP and may provide a promising strategy for predicting the developmental toxicity of related PAHs, without the need for extensive animal testing.

Using quantitative modeling tools to assess pharmacokinetic bias in epidemiological studies showing associations between biomarkers and health outcomes at low exposures

Biomarkers of exposure can be measured at lower and lower levels due to advances in analytical chemistry. Using these sensitive methods, some epidemiology studies report associations between biomarkers and health outcomes at biomarker levels much below those associated with effects in animal studies. While some of these low exposure associations may arise from increased sensitivity of humans compared with animals or from species-specific responses, toxicology studies with drugs, commodity chemicals and consumer products have not generally indicated significantly greater sensitivity of humans compared with test animals for most health outcomes. In some cases, these associations may be indicative of pharmacokinetic (PK) bias, i.e., a situation where a confounding factor or the health outcome itself alters pharmacokinetic processes affecting biomarker levels. Quantitative assessment of PK bias combines PK modeling and statistical methods describing outcomes across large numbers of individuals in simulated populations. Here, we first provide background on the types of PK models that can be used for assessing biomarker levels in human population and then outline a process for considering PK bias in studies intended to assess associations between biomarkers and health outcomes at low levels of exposure. After providing this background, we work through published examples where these PK methods have been applied with several chemicals/chemical classes - polychlorinated biphenyls (PCBs), perfluoroalkyl substances (PFAS), polybrominated biphenyl ethers (PBDE) and phthalates - to assess the possibility of PK bias. Studies of the health effects of low levels of exposure will be improved by developing some confidence that PK bias did not play significant roles in the observed associations.

Physiology-based toxicokinetic modelling in the frame of the European Human Biomonitoring Initiative

Given the opportunities provided by internal dosimetry modelling in the interpretation of human biomonitoring (HBM) data, the assessment of the links between exposure to chemicals and observed HBM data can be effectively supported by PBTK modelling. This paper gives a comprehensive review of available human PBTK models for compounds selected as a priority by the European Human Biomonitoring Initiative (HBM4EU). We highlight their advantages and deficiencies and suggest steps for advanced internal dose modelling. The review of the available PBTK models highlighted the conceptual differences between older models compared to the ones developed recently, reflecting commensurate differences in research questions. Due to the lack of coordinated strategies for deriving useful biomonitoring data for toxicokinetic properties, significant problems in model parameterisation still remain; these are further increased by the lack of human toxicokinetic data due to ethics issues. Finally, questions arise as well as to the extent they are really representative of interindividual variability. QSARs for toxicokinetic properties is a complementary approach for PBTK model parameterisation, especially for data poor chemicals. This approach could be expanded to model chemico-biological interactions such as intestinal absorption and renal clearance; this could serve the development of more complex generic PBTK models that could be applied to newly derived chemicals. Another gap identified is the framework for mixture interaction terms among compounds that could eventually interact in metabolism. From the review it was concluded that efforts should be shifted toward the development of generic multi-compartmental and multi-route models, supported by targeted biomonitoring coupled with parameterisation by both QSAR approach and experimental (in-vivo and in-vitro) data for newly developed and data poor compounds.

Ultrasensitivity dynamics of diverse aryl hydrocarbon receptor modulators in a hepatoma cell line

The aryl hydrocarbon receptor (AhR) is a nuclear receptor that facilitates a wide transcriptional response and causes a variety of adaptive and maladaptive physiological functions. Such functions are entirely dependent on the type of ligand activating it, and therefore, the nuances in the activation of this receptor at the single-cell level have become a research interest for different pharmacological and toxicological applications. Here, we investigate the activation of the AhR by diverse classes of compounds in a Hepa1c1c7-based murine hepatoma cell line. The exogenous compounds analyzed produced different levels of ultrasensitivity in AhR activation as measured by XRE-coupled EGFP production and analyzed by both flow cytometric and computational simulation techniques. Interestingly, simulation experiments reported herein were able to reproduce and quantitate the natural single-cell stochasticity inherent to mammalian cell lines as well as the ligand-specific differences in ultrasensitivity. Classical AhR modulators 2,3,7,8-tetrachlorodibenzodioxin (10^- 1-10⁵ pM), PCB-126 (10^- 1-10⁷ pM), and benzo[a]pyrene (10^- 1-10⁷ pM) produced the greatest levels of single-cell ultrasensitivity and most maximal responses, while consumption-based ligands indole-3-carbinol (10³-10⁹ pM), 3,3'-diindolylmethane (10³-10⁸ pM), and cannabidiol (10³-10⁸ pM) caused low-level AhR activation in more purely graded single-cell fashions. All compounds were tested and analyzed over a 24 h period for consistency. The comparative quantitative results for each compound are presented within. This study aids in defining the disparity between different types of AhR modulators that produce distinctly different physiological outcomes. In addition, the simulation tool developed for this study can be used in future studies to predict the quantitative effects of diverse types of AhR ligands in the context of pharmacological therapies or toxicological concerns.

Early life exposure to air pollution particulate matter (PM) as risk factor for attention deficit/hyperactivity disorder (ADHD): Need for novel strategies for mechanisms and causalities

Epidemiological studies have demonstrated that air pollution particulate matter (PM) and adsorbed toxicants (organic compounds and trace metals) may affect child development already in utero. Recent studies have also indicated that PM may be a risk factor for neurodevelopmental disorders (NDDs). A pattern of increasing prevalence of attention deficit/hyperactivity disorder (ADHD) has been suggested to partly be linked to environmental pollutants exposure, including PM. Epidemiological studies suggest associations between pre- or postnatal exposure to air pollution components and ADHD symptoms. However, many studies are cross-sectional without possibility to reveal causality. Cohort studies are often small with poor exposure characterization, and confounded by traffic noise and socioeconomic factors, possibly overestimating the study associations. Furthermore, the mechanistic knowledge how exposure to PM during early brain development may contribute to increased risk of ADHD symptoms or cognitive deficits is limited. The closure of this knowledge gap requires the combined use of well-designed longitudinal cohort studies, supported by mechanistic in vitro studies. As ADHD has profound consequences for the children affected and their families, the identification of preventable risk factors such as air pollution exposure should be of high priority.