Using publicly available data, a physiologically-based pharmacokinetic model and Bayesian simulation to improve arsenic non-cancer dose-response

Binary toxicity of engineered silica nanoparticles (nSiO2) and arsenic (III) to zebrafish (Danio rerio): application of response surface methodology

Increasing production and use of engineered nanoparticles (NPs) leads to their release into the aquatic environments where they can interact with other hazardous contaminants, such as heavy metals, and threaten aquatic organisms. This study considers the ecotoxicity of arsenic (III) and silica nanoparticles (nSiO₂), individually and simultaneously, to the zebrafish (Danio rerio) using response surface methodology (RSM) under central composite design (CCD). The results revealed that in the treatments within the concentration range of 1 to 5 mg L^-1 arsenic and 1-100 mg L^-1 nSiO₂, no mortality was observed after 96 h. The optimal conditions for achieving the lowest effect of simultaneous toxicity in the concentration range of nSiO₂ and arsenic were 100 and 7 mg L^-1, respectively. Accordingly, the desirable function of the predicted model was found to be 0.78. According to these results, arsenic is toxic for zebrafish. Importantly, exposure to nSiO₂ alone did not cause acute toxicity in the studied species, while arsenic toxicity decreased by increasing the concentration of nSiO₂.

Screening of pesticide distributions in foods of animal origin: a matrix-based approach for biotransfer factor modeling of grazing mammals

Pesticides are detected in a wide array of foods of animal origin, posing a threat to food safety and human health. Here, to facilitate the management of pesticide residues in livestock products, we proposed a screening model for simulating pesticide biotransfer factors (BTFs, ratio of steady-state pesticide concentration between animal tissues and feed) in mammalian bodies. The proposed model was developed based on simple matrix algebra using first-order kinetics. Simulation of over 700 pesticides in common food products derived from cattle and sheep indicated that pesticide biotransfer is a balancing process between uptake efficiency from the gut lumen and the uptake-elimination ratio (ratio of the overall uptake and elimination rate constants) in individual tissues. Furthermore, we parameterized the developed BTF model using the octanol-water partition coefficient. The simulated pesticide BTFs could be categorized into three lipophilicity phases, namely, the lipophilicity-boosting (log K_OW < 4), lipophilicity-balancing (4 ≤ log K_OW ≤ 8), and lipophilicity-limiting (log K_OW > 8) phases, and the simulated general trends of BTFs were consistent with the experimental data. Although the metabolic rate constants of pesticides in mammalian bodies warrant further evaluation, the model proposed here can assist in the risk assessment and regulatory management of pesticide residues in foods of animal origin.

Accumulation, transformation and subcellular distribution of arsenite associated with five carbon nanomaterials in freshwater zebrafish specific-tissues

Although carbon nanomaterials (CNMs) commonly exist throughout the aquatic environment, their effect on arsenic (As) distribution and toxicity is unclear. In this study, arsenite accumulation, transformation, subcellular distribution, and enzyme activity were assessed in adult zebrafish (Danio rerio) intestines, heads and muscles, following co-exposure to arsenite and CNMs with different structures (single-walled carbon nanotubes (SWCNTs), multi-walled carbon nanotubes (MWCNTs), fullerene (C₆₀), graphene oxide (GO), and graphene (GN)). Results show that GN and GO promoted As toxicity in D. rerio, as carriers increasing total As accumulation in the intestine, resulting in arsenite adsorbed by GO and GN being released and transformed mainly into moderately-toxic monomethylarsonic acid (MMA), which was mostly distributed in organelles and metallothionein-like proteins (MTLPs). Moreover, GO and GN influenced As species distribution in D. rerio due to the excellent electron transfer ability. However, the effect was marginal for SWCNT, MWCNT and C₆₀, because of the different structure and suspension stability in fish-culture water. In addition, in the muscle and head tissues, As was mainly distributed in cellular debris in the forms of dimethylarsinic acid (DMA) and arsenobetaine (AsB). These findings help better understand the influence of CNMs on the mechanism of As toxicity in natural aquatic environments.

Arsenic toxicokinetic modeling and risk analysis: Progress, needs and applications

Arsenic (As) poses unique challenges in PBTK model development and risk analysis applications. Arsenic metabolism is complex, adequate information to attribute specific metabolites to particular adverse effects in humans is sparse, and measurement of relevant metabolites in biological media can be difficult. Multiple As PBTK models have been published and used or adapted for use in various exposure and risk analysis applications. These applications illustrate the broad utility of PBTK models for exposure and dose-response analysis, particularly for arsenic where multi-pathway, multi-route exposures and multiple toxic effects are of concern. Arsenic PBTK models have been used together with exposure reconstruction and dose-response functions to estimate risk of specific adverse health effects due to drinking water exposure and consumption of specific foodstuffs (e.g. rice, seafood), as well as to derive safe exposure levels and develop consumption advisories. Future refinements to arsenic PBTK models can enhance the confidence in such analyses. Improved estimates for methylation biotransformation parameters based on in vitro to in vivo extrapolation (IVIVE) methods and estimation of interindividual variability in key model parameters for specific toxicologically relevant metabolites are two important areas for consideration.

Potential Link between Equol Pollution and Field-Observed Intersex in Wild So-iuy Mullets (Mugil soiuy)

Gonadal intersex has been observed in wild fishes and is attributed to endocrine-disrupting chemicals but the specific causes remain controversial. Here, a forensic analysis utilizing field and laboratory studies was conducted to explore the causal agent(s). In a 2008-2009 survey of Liaodong Bay, China, 20.7-33.3% incidences of gonadal intersex were observed in male so-iuy mullets (Mugil soiuy), a wild sentinel fish species. Steroidal estrogen (estrone, 17β-estradiol, estriol, and ethinylestradiol) and phytoestrogen (equol) were detected in seawater where the fishes were collected with median concentrations of 0.42 ng/L (0.02-1.42 ng/L) E2 equivalent (EEQ-E2) and 22.81 ng/L (0.10-155.99 ng/L) equol. A probabilistic model was used to evaluate the ecological risk of these estrogenic chemicals based on their distribution in the field and dose-response relationship from the laboratory surrogate Japanese medaka (Oryzias latipes) fish. The probability of the incidences of gonadal intersex due to equol exposure was estimated to be 13.5 ± 12.1%, which is considerably higher than that for EEQ-E2, (7.2 ± 68.8) × 10^-4. The agonistic activity of equol to the estrogen receptor α of so-iuy mullets was 3.5-fold higher than that to the estrogen receptor α of Japanese medaka, indicating that equol shows a stronger potential for inducing intersex in so-iuy mullets than in medaka. These results demonstrate that equol, rather than steroid estrogens, is a more likely causal agent for the field-observed intersex in male wild so-iuy mullets.

A Hybrid Bayesian Network Framework for Risk Assessment of Arsenic Exposure and Adverse Reproductive Outcomes

Arsenic contamination of drinking water affects more than 137 million people and has been linked to several adverse health effects. The traditional toxicological approach, "dose-response" graphs, are limited in their ability to unveil the relationships between potential risk factors of arsenic exposure for adverse human health outcomes, which are critically important to understanding the risk at low exposure levels of arsenic. Therefore, to provide insight on the potential interactions of different variables of the arsenic exposure network, this study characterizes the risk factors by developing a hybrid Bayesian Belief Network (BBN) model for health risk assessment. The results show that the low inorganic arsenic concentration increases the risk of low birth weight even for low gestational age scenarios. While increasing the mother's age does not increase the low birthweight risk, it affects the distribution between other categories of baby weight. For low MMA% (<4%) in the human body, increasing gestational age decreases the risk of having low birthweight. The proposed BBN model provides 82% sensitivity and 72% specificity in average for different states of birthweight.

Ranking Ecological Risk of Metals to Freshwater Organisms in Lake Taihu, China

Due to the persistence and the high toxicity of metals to many aquatic organisms, metals in aquatic ecosystems have attracted considerable attention. The objective of the present study was to rank metals in Lake Taihu based on the threat they pose to aquatic organisms. The method involved the assessment of the risks of metals to native aquatic organisms and the potential influence of concentration distributions. Both quotient and probabilistic methods were used to rank the risks of arsenic, cadmium, chromium, copper (Cu), mercury, manganese, nickel (Ni), lead, and zinc (Zn). Based on the probabilistic method, Cu, Ni, and Zn were the metals of great concern, with Cu posing the highest risk.

Adsorption of As(V) from Aqueous Solution on Chitosan-Modified Diatomite

A novel chitosan (CS)-modified diatomite (Dt) was prepared by a simple mixture in the mass ratio to remove As(V) from aqueous solution in this research. The CS-modified Dt adsorbent was characterized by scanning electron microscopy (SEM), Fourier-transform infrared spectroscopy (FTIR), and X-ray powder diffraction (XRD) analysis. The parameters to influence the adsorption of As(V) ion were studied under such conditions as kinetics, adsorption isotherm, and pH effect. The results revealed that adsorption of As(V) was initially rapid and the equilibrium time was reached after 40 min. The optimal value of the pH was 5.0 for better adsorption. The equilibrium data were well fitted to the Langmuir isotherm compared to the Freundlich isotherm, and exhibited the highest capacity and removal efficiency of 94.3% under an initial As(V) concentration of 5 mg/L. The kinetic data were well described by the pseudo-second-order model. In addition, 0.1 M NaOH has the best desorption efficiency of As(V) adsorbed on CS-modified Dt, and the removal efficiency of As(V) was still higher than 90% when after six adsorption-desorption cycles. These results showed that the CS-modified Dt could be considered as a potential adsorbent for the removal of As(V) in aqueous solution.

Influence of humic acid on arsenic bioaccumulation and biotransformation to zebrafish: A comparative study between As(III) and As(V) exposure

Previous studies have indicated that natural organic matter in the aquatic environment could affect arsenic bioaccumulation and biotransformation to aquatic organisms. However, the differences between the effects of arsenite and arsenate exposure have not been studied and compared in fish exposure models. In this study, adult zebrafish (Danio rerio) were exposed to 5 mg/L inorganic As solutions, in the presence of a range of humic acid (HA) concentrations (1, 2.5, 5, 10, 20 mg/L) in 96 h waterborne exposure. Results showed that in the presence of HA, total As bioaccumulation was significantly reduced in zebrafish following arsenite exposure, while this reduction was not observed during arsenate exposure. The reduction in total arsenic bioaccumulation for arsenite exposure can be explained by the fact that HA forming a surface coating on the cell surface, hindering transport and internalization. However, this reduction in total As was not observed due to differences in uptake pathways for arsenate exposure. Results also showed that Arsenobetaine (AsB) was the main biotransformation product in zebrafish following inorganic As exposure, accounting for 44.8%-64.7% of extracted arsenic species in all exposure groups. The addition of HA caused levels of MMA and As(III) to decrease, while the distribution of AsB significantly increased in arsenite exposure groups. The increase in AsB could be because the As(III)-HA complex was formed, affecting the methylation of As(III). In contrast, the addition of HA to arsenate exposure groups, did not affect the reduction of As(V) to As(III) and therefore, an increase in the distribution of AsB was not observed in arsenate exposure groups. This study provides useful information on the mechanisms of toxicity, for improved risk assessment of As in natural aquatic environments.

The Bioaccumulation and Tissue Distribution of Arsenic Species in Tilapia

Arsenic is a public concern due to its widespread occurrence and carcinogenicity. Consumption of arsenic-contaminated fish is an important exposure pathway for human health. This study focused on understanding how exposure to arsenic-contaminated fish is informative to human health risk assessment. While the bioaccumulation and tissue distributions of total arsenic concentration in fish are commonly reported, there are limited studies related to the time-course of arsenic species in various tissues. Using the Tilapia as a case, this study aimed to investigate the bioaccumulation and tissue distributions (liver, gastrointestinal (GI), muscle, and gill) of arsenic species in freshwater fish via diet-borne inorganic arsenic exposure. In particular, the Tilapia were exposed to arsenic (III) and As(V) for 32 days. The accumulation of arsenic in all tissues linearly increased with time in the first 10 days’ exposure, while the arsenic levels remained stable in the following 20 days’ exposure. The accumulation of arsenic in tissue followed the sequence of intestine > liver > gill > muscle. Meanwhile, more than 90% of arsenic was converted into organic form in liver, gill, and muscle, while organic arsenic contributed about 30–80% to the total arsenic in the GI. The percentage of organic form in muscle is the highest, followed by gill, liver, and intestine, and arsenobetaine is the main form of organic arsenic. While the exposure profiles of As(III) and As(V) are quite similar, the absorption rate of As(V) is relatively higher than that of As(III). Information provided here can be instrumental for exposure assessment and risk management for arsenic in aquatic environment.

Bioavailability and risk estimation of heavy metal(loid)s in chromated copper arsenate treated timber after remediation for utilisation as garden materials

There is increasing concern about the use of chromated copper arsenate (CCA) treated timber due to the possible leaching of toxic metals or metalloids. CCA-treated timber waste are currently stockpiled across Australia with limited information about their risks to the environment or human health. In this study, the treatment and utilisation of CCA-treated timber waste as garden mulch, garden retaining walls, and soil additive were investigated. Iron materials were used as immobilising agents. The bioavailability of Cr, Cu and As to Spinacia oleracea from CCA-treated timber, before and after treatment, was determined in the context of human health risk assessment. The results showed that the iron-based treatments resulted in significant decreases in the concentrations of Cu and As in spinach grown in CCA-treated timber in soil. Analyses of CCA derived Cu and As in spinach showed that they accumulated in the roots rather than in the leaves. The risks of toxicity to humans varied for different utilisation scenarios and the immobilisation amendments were shown to reduce carcinogenic and non-carcinogenic risks. The information obtained in this study can inform development of utilisation options for CCA-treated timber wastes.

Using mathematical modeling to infer the valence state of arsenicals in tissues: A PBPK model for dimethylarsinic acid (DMAV) and dimethylarsinous acid (DMAIII) in mice

Chronic exposure to inorganic arsenic (iAs), a contaminant of water and food supplies, is associated with many adverse health effects. A notable feature of iAs metabolism is sequential methylation reactions which produce mono- and di-methylated arsenicals that can contain arsenic in either the trivalent (III) or pentavalent (V) valence states. Because methylated arsenicals containing trivalent arsenic are more potent toxicants than their pentavalent counterparts, the ability to distinguish between the +3 and +5 valence states is a crucial property for physiologically based pharmacokinetic (PBPK) models of arsenicals to possess if they are to be of use in risk assessment. Unfortunately, current analytic techniques for quantifying arsenicals in tissues disrupt the valence state; hence, pharmacokinetic studies in animals, used for model calibration, only reliably provide data on the sum of the +3 and +5 valence forms of a given metabolite. In this paper we show how mathematical modeling can be used to overcome this obstacle and present a PBPK model for the dimethylated metabolite of iAs, which exists as either dimethylarsinous acid, (CH3)2AsIIIOH (abbreviated DMAIII) or dimethylarsinic acid, (CH3)2AsV(O)OH (abbreviated DMAV). The model distinguishes these two forms and sets a lower bound on how much of an organ's DMA burden is present in the more reactive and toxic trivalent valence state. We conjoin the PBPK model to a simple model for DMAIII-induced oxidative stress in liver and use this extended model to predict cytotoxicity in liver in response to the high oral dose of DMAV. The model incorporates mechanistic details derived from in vitro studies and is iteratively calibrated with lumped-valence-state PK data for intravenous or oral dosing with DMAV. Model formulation leads us to predict that orally administered DMAV undergoes extensive reduction in the gastrointestinal (GI) tract to the more toxic trivalent DMAIII.

Development of a PBPK Model for Silver Accumulation in Chub Infected with Acanthocephalan Parasites

Simultaneous presence of metals and parasites in fish might lead to potential risks to human health. Parasites might influence metal accumulation and disturb detoxification in fish, thereby affecting biomarkers of fish responses as well as metal biomagnification in humans. It is, therefore, of importance to take into account parasite infection when investigating metal accumulation in fish. However, mechanisms of metal accumulation and distribution in fish-parasite systems are not integrated into current approaches. The present study proposes a new physiologically based pharmacokinetic model for mechanistic simulation of metal partitioning between intestinal parasites and their hosts. As a particular case, Ag accumulation in the system of chub Squalius cephalus and the acanthocephalan Pomphorhynchus tereticollis was investigated. As a novelty, fish cardiac output and organ-specific blood flow distribution were incorporated in our model. This approach distinguishes the current model from the ones developed previously. It also facilitates model extrapolation and application to varying conditions. In general, the model explained Ag accumulation in the system well, especially in chub gill, storage (including skin, muscle, and carcass), and liver. The highest concentration of Ag was found in the liver. The accumulation of Ag in the storage, liver, and gill compartments followed a similar pattern, i.e., increasing during the exposure and decreasing during the depuration. The model also generated this observed trend. However, the model had a weaker performance for simulating Ag accumulation in the intestine and the kidney. Silver accumulation in these organs was less evident with considerable variations.

A Pooled Data Analysis to Determine the Relationship between Selected Metals and Arsenic Bioavailability in Soil

Chronic exposure to arsenic (As) is a global concern due to worldwide exposure and adverse effects, and the importance of incorporating bioavailability in the exposure assessment and risk assessment of As is increasing acknowledged. The bioavailability of As is impacted by a number of soil properties, such as pH, clay and metal concentrations. By retrieving 485 data from 32 publications, the aim of this study was to determine the relationship between selected metals (Fe and Al) and As bioavailability. In present study, the bioaccessibility (BAC) data measured by in vitro approaches were converted into bioavailability data based on the previously determined relationship between BAC and bioavailability. The As relative bioavailability (RBA) was summarized to be 24.36 ± 18.49%, which is in the range previously reported. A significant association between Fe concentration and the bioavailability of As was observed while this association varied for different types of RBA data. This disparity may suggest a non-reliable association between Fe and As bioavailability. The correlations between logarithmically transformed total content of Fe + Al and As bioavailability is then outlined: RBA = (−8.40 ± 1.02) × Ln(Fe + Al) + (58.25 ± 4.09), R² = 0.25, p < 0.001, n = 212. Jackknife resampling was also applied to validate the relation between total content of (Fe + Al) and As bioavailability, which suggested that the relation is robust. This is the first pooled study to address the relations between selected metal concentrations and As bioavailability, which may provide some implications to establish soil properties-based RBA prediction for As.