Impact of biological and environmental variabilities on biological monitoring--an approach using toxicokinetic models

Understanding the binding behavior of Malathion with calf thymus DNA by spectroscopic, cell viability and molecular dynamics simulation techniques: binary and ternary systems comparison

The interaction between calf thymus DNA (ctDNA) and Malathion in the absence and presence of Histone 1 has been enquired by the means of spectroscopic, viscometry, molecular modeling, and cell viability assay techniques. Malathion is capable of quenching the fluorescence of ct DNA in the absence and presence of H1. The binding constants of Malathion-ctDNA complex in the absence of H1 have been calculated to be 6.62 × 10⁴, 4.31 × 10⁴ and 1.93 × 10⁴ M^-1 at 298, 303, and 308 K, respectively that revealed static quenching in complex formation. The observed negative values of enthalpy and entropy changes indicate that the main binding interaction forces were van der Waals force and hydrogen bonding. The binding constant between Malathion and single-stranded ctDNA (ss ctDNA) seemed to be much weaker than that of Malathion and double-stranded ctDNA (ds ctDNA). Furthermore, Malathion can induce detectable alterations in the CD spectrum of ctDNA, along with changes in its viscosity. In the presence of H1, fluorescence quenching of ctDNA-Malathion complex displays dynamic behavior and binding constants were perceived to be 1.66 × 10⁴, 2.93 × 10⁴ and 5.77 × 10⁴ M^-1 at 298, 303, and 308 K, respectively. The different of interaction behavior between ctDNA and Malathion in the absence and presence of H1 clearly revealed H1 role in the complex formation and forces change between ctDNA and Malathion. The positive values of enthalpy and entropy changes have suggested that binding process is primarily driven by hydrophobic interactions. The tendency to interact with ss ctDNA, reduced viscosity have designated that the Malathion bound to ctDNA in the presence of H1 is groove binding. The results of molecular docking and molecular dynamics simulation also confirmed potent interactions between Malathion and the macromolecules in the binary and ternary systems.Communicated by Ramaswamy H. Sarma.

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.

Organochlorine and organophosphorus pesticides and bladder cancer: A case-control study

BACKGROUND

Exposure to pesticides is associated with an increase in the incidence of cancer. We aimed to investigate the association of serum organochlorine pesticides (OCPs) and organophosphorus pesticides (OPs) levels and GSTM1/GSTT1 gene polymorphism with bladder cancer (BC).

METHODS

This study was performed on 57 patients with BC and 30 controls (C). Acetylcholinesterase (AChE) activity, arylesterase activity of paraoxonase-1 (ARE), total antioxidant capacity (TAC), and malondialdehyde (MDA) levels were determined in serums of all participants. Genomic DNA was extracted using the salting out method and GSTM1/GSTT1 gene polymorphisms were examined by multiplex polymerase chain reaction assay. Measurement of OCPs (α-hexachlorocyclohexane [α-HCH], β-HCH, γ-HCH, 2,4-dichlorodiphenyltrichloroethane [2,4-DDT], 4,4-DDT, 2,4- dichlorodiphenyldichloroethylene [2,4-DDE], and 4,4-DDE) in serum was carried out using an FID-equipped gas-chromatography system.

RESULTS

AChE activity was significantly lower, ARE activity and TAC were declined but it was not statistically significant, however, α-HCH, γ-HCH, 4,4-DDE, 2,4-DDT, and 4,4-DDT pesticides, and MDA were significantly higher in BC patients compared with the control subjects. Also, a positive correlation was found between the number of smoked cigarettes and the years of smoking with BC development. There was no association between GSTM1/GSTT1 gene polymorphisms and OCPs in BC patients.

CONCLUSION

Due to the higher levels of some OCPs in the BC patients, along with the reduction in AChE activity and increased MDA levels, it may be concluded that OCPs and OPs play an important role in the induction of BC in southeastern Iran.

Derivation of biomonitoring equivalent for inorganic tin for interpreting population-level urinary biomonitoring data

Population-level biomonitoring of tin in urine has been conducted by the U.S. National Health and Nutrition Examination Survey (NHANES) and the National Nutrition and Health Study (ENNS - Étude nationale nutrition santé) in France. The general population is predominantly exposed to inorganic tin from the consumption of canned food and beverages. The National Institute for Public Health and the Environment of the Netherlands (RIVM) has established a tolerable daily intake (TDI) for chronic exposure to inorganic tin based on a NOAEL of 20 mg/kg bw per day from a 2-year feeding study in rats. Using a urinary excretion fraction (0.25%) from a controlled human study along with a TDI value of 0.2 mg/kg bw per day, a Biomonitoring Equivalent (BE) was derived for urinary tin (26 μg/g creatinine or 20 μg/L urine). The geometric mean and the 95th percentile tin urine concentrations of the general population in U.S. (0.705 and 4.5 μg/g creatinine) and France (0.51 and 2.28 μg/g creatinine) are below the BE associated with the TDI, indicating that the population exposure to inorganic tin is below the exposure guidance value of 0.2 mg/kg bw per day. Overall, the robustness of pharmacokinetic data forming the basis of the urinary BE development is medium. The availability of internal dose and kinetic data in the animal species forming the basis of the assessment could improve the overall confidence in the present assessment.

Sex differences in urinary levels of several biological indicators of exposure: a simulation study using a compartmental-based toxicokinetic model

Toxicokinetic modeling is a useful tool to describe or predict the behavior of a chemical agent in the human or animal organism. A general model based on four compartments was developed in a previous study to quantify the effect of human variability on a wide range of biological exposure indicators. The aim of this study was to adapt this existing general toxicokinetic model to three organic solvents--methyl ethyl ketone, 1-methoxy-2-propanol, and 1,1,1,-trichloroethane--and to take into account sex differences. In a previous human volunteer study we assessed the impact of sex on different biomarkers of exposure corresponding to the three organic solvents mentioned above. Results from that study suggested that not only physiological differences between men and women but also differences due to sex hormones levels could influence the toxicokinetics of the solvents. In fact the use of hormonal contraceptive had an effect on the urinary levels of several biomarkers, suggesting that exogenous sex hormones could influence CYP2E1 enzyme activity. These experimental data were used to calibrate the toxicokinetic models developed in this study. Our results showed that it was possible to use an existing general toxicokinetic model for other compounds. In fact, most of the simulation results showed good agreement with the experimental data obtained for the studied solvents, with a percentage of model predictions that lies within the 95% confidence interval varying from 44.4 to 90%. Results pointed out that for same exposure conditions, men and women can show important differences in urinary levels of biological indicators of exposure. Moreover, when running the models by simulating industrial working conditions, these differences could be even more pronounced. A general and simple toxicokinetic model, adapted for three well-known organic solvents, allowed us to show that metabolic parameters can have an important impact on the urinary levels of the corresponding biomarkers. These observations give evidence of an interindividual variability, an aspect that should have its place in the approaches for setting limits of occupational exposure.

Accounting for the impact of short-term variations in the levels of trihalomethane in drinking water on exposure assessment for epidemiological purposes. Part II: biological aspects

The variability of trihalomethane (THM) levels in drinking water raises the question of whether or not short-term variations (within-day) should be accounted for when assessing exposure to contaminants suspected of being carcinogenic and reprotoxic agents. The purpose of this study was to determine the magnitude of the impact on predicted biological levels of THMs (internal doses) exerted by within-day variations of THMs in drinking water. A database extracted from a campaign in the Québec City distribution system served to produce 81, 79 and 64 concentration profiles for the three most abundant THMs, namely chloroform (TCM), dichlorobromomethane (DCBM) and chlorodibromomethane (CDBM), respectively. Using a physiologically based toxicokinetic modeling approach, we simulated exposures (1.5 l water per day and a 10-min shower) based on each of these profiles and predicted, for 2000 individuals (Monte-Carlo simulations), maximum blood concentrations (Cmax), areas under the time versus blood concentrations curve (24 h-AUCcv) and total absorbed doses (ADs). Three different hypotheses were tested: [A] assuming a constant THM concentration in water (e.g., mean value of a day); [B] accounting for within-day variations in THM levels; and [C] a worst-case scenario assuming within-day variations and showering while THM levels were maximal. For each exposure profile, exposure indicator and individual, we calculated the ratios of values obtained according to each hypothesis (e.g., CmaxB/CmaxA and CmaxC/CmaxA) and the values corresponding to the 5th and 95th percentiles of these ratios. The closer these percentiles are to the value of 1, the smaller the error associated with assuming constant THM concentrations rather than their actual variability. Results showed that the minimal gap between these percentiles was TCM-AD(B)/TCM-AD(A) (5th=0.91; 95th=1.09), whereas the maximal gap was CDBM-Cmax(C)/CDBM-Cmax(A) (5th=0.50; 95th=3.40). Overall, TCM and ADs were the less affected (TCM<DCBM<CDBM and AD<AUCcv<Cmax) when accounting for within-day variations in water levels.

Evaluation of occupational exposure: comparison of biological and environmental variabilities using physiologically based toxicokinetic modeling

PURPOSE

Few studies compare the variabilities that characterize environmental (EM) and biological monitoring (BM) data. Indeed, comparing their respective variabilities can help to identify the best strategy for evaluating occupational exposure. The objective of this study is to quantify the biological variability associated with 18 bio-indicators currently used in work environments.

METHOD

Intra-individual (BV(intra)), inter-individual (BV(inter)), and total biological variability (BV(total)) were quantified using validated physiologically based toxicokinetic (PBTK) models coupled with Monte Carlo simulations. Two environmental exposure profiles with different levels of variability were considered (GSD of 1.5 and 2.0).

RESULTS

PBTK models coupled with Monte Carlo simulations were successfully used to predict the biological variability of biological exposure indicators. The predicted values follow a lognormal distribution, characterized by GSD ranging from 1.1 to 2.3. Our results show that there is a link between biological variability and the half-life of bio-indicators, since BV(intra) and BV(total) both decrease as the biological indicator half-lives increase. BV(intra) is always lower than the variability in the air concentrations. On an individual basis, this means that the variability associated with the measurement of biological indicators is always lower than the variability characterizing airborne levels of contaminants. For a group of workers, BM is less variable than EM for bio-indicators with half-lives longer than 10-15 h.

CONCLUSION

The variability data obtained in the present study can be useful in the development of BM strategies for exposure assessment and can be used to calculate the number of samples required for guiding industrial hygienists or medical doctors in decision-making.