Influence of exposure time on toxicity-An overview.

Data on toxicity of chemicals is usually reported as the LD50, or LC50, with the exposure time from experimental testing in the laboratory reported. But the exposure time is not considered to be a quantifiable variable which can be used to evaluate its importance in expressed toxicity, often described in general terms such as acute, chronic and so on. For the last hundred years Habers Rule has been successfully used to extrapolate from reported exposure times to other exposure times which may be needed for setting standards, health risk assessments and other applications. But it has limitations particularly in environmental applications where exposure levels are low and exposure times are relatively long. The Reduced Life Expectancy (RLE) model overcomes these problems and can be utilised under all exposure conditions. It can be expressed as ln(LT50)=-a (LC50)(ν)+b where the constants ν, a and b can be evaluated by fitting the model to experimental data on the LC50, and corresponding LT50, together with the Normal Life Expectancy (NLE) of the organism being considered as a data point when the LC50 is zero. The constant, ν, at a value of unity gives a linear relationship and where ν<1 the relationship has a concave shape. In our extensive evaluations of the RLE model for fish, invertebrates and mammals involving 115 data sets and with a wide range of organic and inorganic toxicants the RLE model gave correlation coefficients of >0.8 with 107 sets of data. The RLE model can be used to extrapolate from a limited data set on exposure times and corresponding LT50 values to any exposure time and corresponding LT50 value. The discrepancy between Haber's Rule and RLE model increases as the exposure time increases.

A comparison of Reduced Life Expectancy (RLE) model with Haber's Rule to describe effects of exposure time on toxicity.

The Reduced Life Expectancy (RLE) Model (LC50 = [ln(NLE) - ln(LT50)]/d) has been proposed as an alternative to Haber's Rule. The model is based on a linear relationship between LC50 (Lethal Exposure Concentration) and lnLT50 (Lethal Exposure Time) and uses NLE (Normal Life Expectancy) as a limiting point as well as a long term data point (where d is a constant). The purposes of this paper were to compare the RLE Model with Haber's Rule with available toxicity data and to evaluate the strengths and weaknesses of each approach. When LT50 is relatively short and LC50 is high, Haber's Rule is consistent with the RLE model. But the difference between the two was evident in the situation when LT50 is relatively long and LC50 is low where the RLE model is a marked departure from Haber's Rule. The RLE Model can be used to appropriately evaluate long term effects of exposure.

Evaluation of effects of long term exposure on lethal toxicity with mammals.

The relationship between exposure time (LT50) and lethal exposure concentration (LC50) has been evaluated over relatively long exposure times using a novel parameter, Normal Life Expectancy (NLT), as a long term toxicity point. The model equation, ln(LT50) = aLC50(ν) + b, where a, b and ν are constants, was evaluated by plotting lnLT50 against LC50 using available toxicity data based on inhalation exposure from 7 species of mammals. With each specific toxicant a single consistent relationship was observed for all mammals with ν always <1. Use of NLT as a long term toxicity point provided a valuable limiting point for long exposure times. With organic compounds, the Kow can be used to calculate the model constants a and v where these are unknown. The model can be used to characterise toxicity to specific mammals and then be extended to estimate toxicity at any exposure time with other mammals.

Reduced life expectancy model for effects of long term exposure on lethal toxicity with fish.

A model based on the concept of reduction in life expectancy (RLE model) as a result of long term exposure to toxicant has been developed which has normal life expectancy (NLT) as a fixed limiting point for a species. The model is based on the equation (LC50 = a ln(LT50) + b) where a and b are constants. It was evaluated by plotting ln LT50 against LC50 with data on organic toxicants obtained from the scientific literature. Linear relationships between LC50 and ln LT50 were obtained and a Calculated NLT was derived from the plots. The Calculated NLT obtained was in good agreement with the Reported NLT obtained from the literature. Estimation of toxicity at any exposure time and concentration is possible using the model. The use of NLT as a reference point is important since it provides a data point independent of the toxicity data set and limits the data to the range where toxicity occurs. This novel approach, which represents a departure from Haber's rule, can be used to estimate long term toxicity from limited available acute toxicity data for fish exposed to organic biocides.

Evaluation of effects of exposure time on aquatic toxicity with zooplanktons using a reduced life expectancy model.

Traditionally in toxicological studies time is not studied as quantifiable variable but as a fixed endpoint. The Reduced Life Expectancy (RLE) model which relates exposure time and exposure concentration with lethal toxic effects was tested previously using fish data. In this current paper the effects of exposure time on aquatic toxicity with zooplanktons and various toxicants were evaluated using the RLE model based on ambient exposure concentration. The model was evaluated by plotting lnLT(50) against LC(50) using toxicity data with zooplanktons from the literature for metal, metalloid and organic compounds. Most of the experimental data sets can be satisfactorily correlated by use of the RLE model, but deviations occurred for some data sets. Those data sets were satisfactorily fitted by a two stage RLE model. This model was based on two phases: one in the peripheral system and other in the central system. Both the single and two stage RLE model support the hypothesis that toxicity is time dependent and decreases in a systematic way with increasing exposure time. A calculated normal life expectancy (NLT) can be obtained from the single stage model and is in accord with reported NLT but those obtained from the two stage RLE model are in excellent agreement.

Health risk characterisation for environmental pollutants with a new concept of overall risk probability.

In health risk assessment, risk is commonly characterised by calculating a simple hazard quotient (HQ), which cannot reflect the actual distribution of exposure and health effect values. This study aimed to develop a new risk characterisation method, the overall risk probability (ORP) method based on probabilistic techniques. Exposure exceedence values were calculated to obtain an exposure exceedence curve (EEC). The area under the EEC was calculated as the ORP value to represent the risk. This method was demonstrated by a case study for two steroidal EDCs, 17ß-estradiol (E2) and 17α-ethinylestradiol (EE2) for fish in surface water. It was found that the risk probability of fish exposed to E2 (ORP, 8.1%) and EE2 (ORP, 27%) were both above the reference value of 2.5%, which was consistent with the results of HQ method. Assuming independent action of individual EDCs, a combined risk probability of 33% was obtained for the mixture effects of E2 and EE2. Our results implicated that the adverse health effects imposed by E2 and EE2 were significant for fish in surface water worldwide.

An overall risk probability-based method for quantification of synergistic and antagonistic effects in health risk assessment for mixtures: theoretical concepts.

PURPOSE: In the assessment of health risks of environmental pollutants, the method of dose addition and the method of independent action are used to assess mixture effects when no synergistic and/or antagonistic effects are present. Currently, no method exists to quantify synergistic and/or antagonistic effects for mixtures. The purpose of this paper is to develop the theoretical concepts of an overall risk probability (ORP)-based method to quantify the synergistic and antagonistic effects in health risk assessment for mixtures. METHOD: The ORP for health effects of environmental chemicals was determined from the cumulative probabilities of exposure and effects. This method was used to calculate the ORP for independent mixtures and for mixtures with synergistic and antagonistic effects. RESULTS: For the independent mixtures, a mixture ORP can be calculated from the product of the ORPs of individual components. For systems of interacting mixtures, a synergistic coefficient and an antagonistic coefficient were defined respectively to quantify the ORPs of each individual component in the mixture. The component ORPs with synergistic and/or antagonistic effects were then used to calculate the total ORP for the mixture. CONCLUSIONS: An ORP-based method was developed to quantify synergistic and antagonistic effects in health risk assessment for mixtures. This represents a first method to generally quantify mixture effects of interacting toxicants.

Fate simulation and risk assessment of endocrine disrupting chemicals in a reservoir receiving recycled wastewater.

A fugacity based model was applied to simulate the distribution of three endocrine disrupting chemicals (EDCs), namely estrone (E1), 17ß-estradiol (E2) and 17α-ethynylestradiol (EE2) in a reservoir receiving recycled wastewater in Australia. At typical conditions, the majority of estrogens were removed by degradation in the water compartment. A sensitivity analysis found that the simulated concentrations of E1, E2 and EE2 were equally sensitive to the parameters of temperature (T), reservoir water volume (V) and equivalent biomass concentration (EBC), but E1 was more sensitive to estrogen concentration in the recycled water (C(e)) and recycling rate (F(r)). In contrast, all three estrogens were not sensitive to reservoir water releasing rate (F(d)). Furthermore, a probabilistic health risk assessment showed that the simulated concentrations were below fish exposure threshold value (ETV) and human public health standard (PHS). Human equivalent dose of EDCs from fish consumption was about 10 times higher than that from drinking water consumption. The highest risk quotient among the three estrogens was found for EE2 with less than 9.5×10(-2), implying negligible health risks.

Quantitative structure-property relationships (QSPR) for steroidal compounds of environmental importance.

A quantitative structure-property relationships (QSPR) study was carried out for 17 steroidal compounds using calculated molecular descriptors and measured properties. The utility of calculated molecular descriptors and properties was evaluated and improved in some instances by subgroup classification of these 17 compounds into estrogens and androgens. The calculated values for the octanol-water partition coefficient (logK(ow)) were found to be in good agreement with the measured values for all 17 compounds, whilst good agreement between the calculated and measured values for aqueous solubility (logS) was found only for the subgroup of androgens. Good linear relationships (R(2)0.782) were found between measured logK(ow) values and three molecular descriptors (logFOSA, hydrophobic component of the total solvent accessible surface area; logFISA, hydrophilic component of the total solvent accessible area and logPSA, Van de Waals surface area of polar nitrogen and oxygen atoms). For the measured logS values, only weak correlations with molecular descriptors were observed (R(2)0.505). The coefficient of logS in the relationship with the hydrophobic parameter (logFOSA) was negative but positive with the hydrophilic parameters (logFISA and logPSA). Conversely with logK(ow) the opposite was found. These observations are in accord with the effects of molecular polarity on aqueous solubility.

Human health risk assessment of chlorinated disinfection by-products in drinking water using a probabilistic approach.

The presence of chlorinated disinfection by-products (DBPs) in drinking water is a public health issue, due to their possible adverse health effects on humans. To gauge the risk of chlorinated DBPs on human health, a risk assessment of chloroform (trichloromethane (TCM)), bromodichloromethane (BDCM), dibromochloromethane (DBCM), bromoform (tribromomethane (TBM)), dichloroacetic acid (DCAA) and trichloroacetic acid (TCAA) in drinking water was carried out using probabilistic techniques. Literature data on exposure concentrations from more than 15 different countries and adverse health effects on test animals as well as human epidemiological studies were used. The risk assessment showed no overlap between the highest human exposure dose (EXP(D)) and the lowest human equivalent dose (HED) from animal test data, for TCM, BDCM, DBCM, TBM, DCAA and TCAA. All the HED values were approximately 10(4)-10(5) times higher than the 95th percentiles of EXP(D). However, from the human epidemiology data, there was a positive overlap between the highest EXP(D) and the lifetime average daily doses (LADD(H)) for TCM, BDCM, DCAA and TCAA. This suggests that there are possible adverse health risks such as a small increased incidence of cancers in males and developmental effects on infants. However, the epidemiological data comprised several risk factors and exposure classification levels which may affect the overall results.

Occurrence and seasonal variations of algal toxins in water, phytoplankton and shellfish from North Stradbroke Island, Queensland, Australia.

A number of marine microalgae are known to produce toxins that can accumulate in shellfish and when eaten, lead to toxic and potentially fatal reactions in humans. This paper reports on the occurrence and seasonal variations of algal toxins in the waters, phytoplankton and shellfish of Southeast Queensland, Australia. These algal toxins include okadaic acid (OA), domoic acid (DA), gymnodimine (GD), pectenotoxin-2 (PTX-2) and pectenotoxin-2-seco acid (PTX-2-SA), which were detected in the sampled shellfish and phytoplankton, via HPLC-MS/MS. Dissolved OA, PTX-2 and GD were also detected in the samples collected from the water column. This was the first occasion that DA and GD have been reported in shellfish, phytoplankton and the water column in Queensland waters. Phytoplankton tows contained both the toxic Dinophysis and Pseudo-nitzschia algae species, and are suspected of being the most likely producers of the OA, PTX-2s and DA found in shellfish of this area. The number of cells, however, did not correlate with the amount of toxins present in either shellfish or phytoplankton. This indicates that toxin production by algae varies with time and the species present and that number of cells alone cannot be used as an indicator for the presence of toxins. The presence of OA and PTX-2s were more frequently seen in the summer, while DA and GD were detected throughout the year and without any obvious seasonal patterns.