Approach for extrapolating in vitro metabolism data to refine bioconcentration factor estimates

National and international chemical management programs are assessing thousands of chemicals for their persistence, bioaccumulative and environmental toxic properties; however, data for evaluating the bioaccumulation potential for fish are limited. Computer based models that account for the uptake and elimination processes that contribute to bioaccumulation may help to meet the need for reliable estimates. One critical elimination process of chemicals is metabolic transformation. It has been suggested that in vitro metabolic transformation tests using fish liver hepatocytes or S9 fractions can provide rapid and cost-effective measurements of fish metabolic potential, which could be used to refine bioconcentration factor (BCF) computer model estimates. Therefore, recent activity has focused on developing in vitro methods to measure metabolic transformation in cellular and subcellular fish liver fractions. A method to extrapolate in vitro test data to the whole body metabolic transformation rates is presented that could be used to refine BCF computer model estimates. This extrapolation approach is based on concepts used to determine the fate and distribution of drugs within the human body which have successfully supported the development of new pharmaceuticals for years. In addition, this approach has already been applied in physiologically-based toxicokinetic models for fish. The validity of the in vitro to in vivo extrapolation is illustrated using the rate of loss of parent chemical measured in two independent in vitro test systems: (1) subcellular enzymatic test using the trout liver S9 fraction, and (2) primary hepatocytes isolated from the common carp. The test chemicals evaluated have high quality in vivo BCF values and a range of logK(ow) from 3.5 to 6.7. The results show very good agreement between the measured BCF and estimated BCF values when the extrapolated whole body metabolism rates are included, thus suggesting that in vitro biotransformation data could effectively be used to reduce in vivo BCF testing and refine BCF model estimates. However, additional fish physiological data for parameterization and validation for a wider range of chemicals are needed.     

First report on development of quantitative interspecies structure-carcinogenicity relationship models and exploring discriminatory features for rodent carcinogenicity of diverse organic chemicals using OECD guidelines

Different regulatory agencies in food and drug administration and environmental protection worldwide are employing quantitative structure-activity relationship (QSAR) models to fill the data gaps related with properties of chemicals affecting the environment and human health. Carcinogenicity is a toxicity endpoint of major concern in recent times. Interspecies toxicity correlations may provide a tool for estimating sensitivity towards toxic chemical exposure with known levels of uncertainty for a diversity of wildlife species. In this background, we have developed quantitative interspecies structure-carcinogenicity correlation models for rat and mouse [rodent species according to the Organization for Economic Cooperation and Development (OECD) guidelines] based on the carcinogenic potential of 166 organic chemicals with wide diversity of molecular structures, spanning a large number of chemical classes and biological mechanisms. All the developed models have been assessed according to the OECD principles for the validation of QSAR models. Consensus predictions for carcinogenicity of the individual compounds are presented here for any one species when the data for the other species are available. Informative illustrations of the contributing structural fragments of chemicals which are responsible for specific carcinogenicity endpoints are identified by the developed models. The models have also been used to predict mouse carcinogenicities of 247 organic chemicals (for which rat carcinogenicities are present) and rat carcinogenicities of 150 chemicals (for which mouse carcinogenicities are present). Discriminatory features for rat and mouse carcinogenicity values have also been explored.     

A new hybrid system of QSAR models for predicting bioconcentration factors (BCF)

The aim was to develop a reliable and practical quantitative structure–activity relationship (QSAR) model validated by strict conditions for predicting bioconcentration factors (BCF). We built up several QSAR models starting from a large data set of 473 heterogeneous chemicals, based on multiple linear regression (MLR), radial basis function neural network (RBFNN) and support vector machine (SVM) methods. To improve the results, we also applied a hybrid model, which gave better prediction than single models. All models were statistically analysed using strict criteria, including an external test set. The outliers were also examined to understand better in which cases large errors were to be expected and to improve the predictive models. The models offer more robust tools for regulatory purposes, on the basis of the statistical results and the quality check on the input data.     

A new hybrid system of QSAR models for predicting bioconcentration factors (BCF)

The aim was to develop a reliable and practical quantitative structure-activity relationship (QSAR) model validated by strict conditions for predicting bioconcentration factors (BCF). We built up several QSAR models starting from a large data set of 473 heterogeneous chemicals, based on multiple linear regression (MLR), radial basis function neural network (RBFNN) and support vector machine (SVM) methods. To improve the results, we also applied a hybrid model, which gave better prediction than single models. All models were statistically analysed using strict criteria, including an external test set. The outliers were also examined to understand better in which cases large errors were to be expected and to improve the predictive models. The models offer more robust tools for regulatory purposes, on the basis of the statistical results and the quality check on the input data.     

Uptake rates of alkylphenols, PAHs and carbazoles in semipermeable membrane devices (SPMDs) and polar organic chemical integrative samplers (POCIS)

Passive sampling devices provide a useful contribution to the monitoring of contaminants in the aquatic environment. However, calibration data needed for the calculation of water concentrations from sampler accumulations are restricted to a limited number of compound classes. Thus uptake of a range of alkylated phenols (AP), polycyclic aromatic hydrocarbons (PAH) and carbazoles was determined for semipermeable membrane devices (SPMDs) and polar organic chemical integrative samplers (POCIS) using a flow through exposure system. Sampling rates ranged from 0.02 to 0.26 l d(-1) for POCIS and 0.02 to 13.83 l d(-1) for SPMDs. Observed SPMD uptake was also compared to that predicted by an empirical model including the use of performance reference compounds (PRCs). Predicted sampling rates did not differ by more than a factor of 1.3 from experimental values for PAH, providing further evidence that the PRC approach can be successfully used to determine in situ sampling rates for these compounds. Experimental sampling rates for AP in SPMDs were, however, much lower than predicted. This discrepancy was too large to be explained by small uncertainties in the calibration system or in the calculations. Based on these data we conclude that while hydrophobic AP are accumulated by SPMDs their partitioning cannot be predicted from their logK(ow) using current methods. Due to this lower than expected uptake, sampling rates were only higher in SPMDs than POCIS in the range of logK(ow)>5.0. Simultaneous deployment of both sampler types allows the study of compounds with a broad range of physicochemical properties.     

Physical origin for the nonlinear sorption of very hydrophobic organic chemicals in a membrane-like polymer film

Bioconcentration factor (BCF) is often assumed to be linearly associated with the octanol-water partition coefficient K(ow) for hydrophobic organic chemicals (HOCs). However, a large amount of data has suggested that the correlation between the logBCF and logK(ow) is curvilinear for HOCs. Similar curvilinear relationship has also been noticed for sorption of HOCs into poly(dimethyl)siloxane (PDMS), a polymer with cross-linked interior structures. So far no satisfactory explanation has been given to account for the deviation. In this study, we acquired additional experimental data to show that the curvilinear relationship between the log-based PDMS-coated fiber-water partition coefficient (logK(f)) and logK(ow) for polychlorinated biphenyls (PCBs) was indeed a reflection of the sorption process occurring in PDMS film other than experimental defects. The physical origin of the nonlinearity was pinpointed based on the theory of phase partitioning for HOCs. The linear relationship is observed if the solute molecule is considerably smaller than the size of a monomer unit of PDMS in that the Gibbs free energy required for cavity formation in PDMS is comparable to that in octanol. Higher free energy of cavity formation is needed to create sufficient free volume if the PCB molecular size is comparable to or larger than the monomer unit of PDMS. On the other hand, the free energy of cavity formation in octanol remains almost constant when this occurs, resulting in the observed curvilinear relationship. The proposed model adequately explains the observed data, as well as sheds lights into the physical origin of the steric interactions of large molecular size solute with the PDMS polymer network.     

Partitioning of selected environmental pollutants into organic matter as determined by solid-phase microextraction

Partitioning/sorption of selected environmental pollutants (PCBs, organochlorine insecticides, triazine and amide herbicides) into dissolved humic acids (HA), soil and mineral substances was evaluated by measuring their free concentrations by solid-phase microextraction (SPME). Compounds were chosen to cover a wide range of logK(ow) (2.2-7.6). Two different types of partitioning behaviour for dissolved HA were observed. Compounds with logK(ow)>5 partitioned almost instantly into HA fraction and the remaining free fraction remained rather constant. LogK(HA) and logK(DOC) were calculated and found to be similar for commercial HA, HA standard and isolated HA. The behaviour of these compounds in soil suspension was similar, but strong sorption on CaCO3 and Florisil was also noticed. For compounds with logK(ow)<5, we have not noticed significant changes in free concentrations in HA solutions over time. In soil suspension, however, some sorption/partitioning was observed over time for some compounds, but it was matching the sorption on CaCO3 and Florisil.     

Estimating K(oc) for persistent organic pollutants: limitations of correlations with K(ow)

The n-octanol/water partition coefficient (K(ow)) is commonly used to predict the soil or aquatic particle water partition coefficient normalized to organic carbon (K(oc)). Many correlations are available covering several chemical classes and ranges of hydrophobicity. This work indicates the K(ow) may not be a strong predictor for persistent organic pollutants (POPs) which are defined here as chemicals with logK(ow) > 5.0. In addition, the correlation developed in this work for POPs will still result in a predicted value which is of by a factor of 15. Accordingly, care must be taken when applying K(oc) estimations using K(ow) for POPs until more suitable correlations are developed.     

Strategies for including vegetation compartments in multimedia models

The incentives for including vegetation compartments in multimedia Level I, II and III fugacity calculations are discussed and equations and parameters for undertaking the calculations suggested. Model outputs with and without vegetation compartments are compared for 12 non-ionic organic chemicals with a wide variety of physical-chemical properties. Inclusion of vegetation compartments is shown to have a significant effect on two classes of chemicals: (1) those that are taken up by atmospheric deposition and (2) those that are taken up by transpiration through the plant roots. It is suggested that uptake from the atmosphere is important for chemicals with logK(OA) greater than 6 and a logK(AW) of greater than -6. Plant uptake by transpiration is important for chemicals with logK(OW) less than 2.5 and a logK(AW) of less than -1. At logK(OA) > 9 atmospheric uptake is dominated by particle-bound deposition and the importance of partitioning to vegetation is largely dependent on the relative magnitude of the particle deposition velocities to soil and vegetation. These property ranges can be used to determine if a chemical will significantly partition to vegetation. If the chemical falls outside the property ranges of the two classes it will probably be unnecessary to include vegetation in models for assessing environmental fate. The amount of chemical predicted to partition to vegetation compartments in the model is shown to be highly sensitive to certain model assumptions. Further experimental research is recommended to obtain more reliable equations describing equilibrium partitioning and uptake/depuration kinetics.     

Acute toxicity of substituted phenols to Rana japonica tadpoles and mechanism-based quantitative structure-activity relationship (QSAR) study.

Acute 12 h and 24 h lethal toxicity (12 h-LC50 and 24 h-LC50) of 31 substituted phenols to Rana japonica tadpoles was determined. Results indicate that toxicity of phenols to tadpoles varied only slightly with length of exposure and the 12-h test could serve as surrogate of the 24-h test. A mechanism-based quantitative structure-activity relationship (QSAR) method was employed and 1-octanol/water partition coefficient (log K(ow))-dependent models were developed to study different modes of toxic action. Most phenols elicited their response via a polar narcotic mechanism and an excellent logK(ow)-dependent model was obtained. Soft electrophilicity and pro-electrophilicity were observed for some phenols and a good log K(ow)-dependent model was also achieved. Additionally, the significant dissociation of carboxyl on benzoic acid derivatives sharply reduced their toxicity. A statistically robust QSAR model was developed for all studied compounds with the combined application of log K(ow), energy of lowest unoccupied orbital (E(lumo)), heat of formation (HOF) and the first-order path molecular connectivity dices (1chi(p)).     

Calculation of environmental concentration and comparison of output for existing chemicals using regional multimedia modeling

The environmental fate of 40 existing chemicals is discussed using the EUSES multimedia distribution and risk assessment model with site-specific parameter setting in an urban area of Japan including a highly industrial region. There has been a strong need to assess the environmental fate of a huge number of existing chemicals. Data on the emission amounts of chemicals are essential for such prediction, and PRTR surveys may yield this data. The study delivered the following results: (1) Volatile compounds with large amounts of emission showed higher predicted concentrations in air, and the concentrations of several compounds agreed well with averaged monitoring data within an order of magnitude. (2) A close relationship was found between the concentration of water and that of sediment, suggesting that the fate of chemicals in sediment essentially depended on the water environment. (3) A group of volatile solvents had high mass distribution ratio to air. Some compounds having high solubility in water were also included in that group due to the high ratio of air emission. Highly hydrophobic compounds with logK(OW) larger than 6.0 showed a high distribution ratio to soil and sediment. (4) Volatile compounds were mostly taken through air. The exposure through fish is a dominant pathway for highly hydrophobic compounds. (5) Exposure ratio could be gathered from physicochemical properties. The exposure from fish intake was roughly estimated by logK(OW), whereas exposure from air and water intake was difficult to estimate simply by vapor pressure and solubility in water, respectively.