Predicted toxicity of naphthenic acids present in oil sands process-affected waters to a range of environmental and human endpoints

Science of the Total Environment 425 (2012) 119–127

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Predicted toxicity of naphthenic acids present in oil sands process-affected waters to a range of environmental and human endpoints Alan G. Scarlett a,⁎, Charles E. West a, David Jones a, Tamara S. Galloway b, Steven J. Rowland a a b

Petroleum & Environmental Geochemistry Group, Biogeochemistry Research Centre, University of Plymouth, Plymouth, PL4 8AA, Devon, UK Biosciences, College of Life and Environmental Sciences, University of Exeter, Stocker Road, Exeter, EX4 4QD, UK

a r t i c l e

i n f o

Article history: Received 9 November 2011 Received in revised form 20 February 2012 Accepted 26 February 2012 Available online 29 March 2012 Keywords: Petroleum Naphthenic acid Liver enzymes Endocrine disruption Athabasca oil sands Toxicity model

a b s t r a c t Naphthenic acids (NAs) are considered to be a major toxic component of oil sands process-affected waters (OSPW) and are also widely used for industrial processes. The effects of previously identified NAs (54 in total), together with six alkylphenols, were modelled for a range of environmental and human toxicity related endpoints using ADMET predictor™ software. In addition to the models, experimental CALUX® assays were performed on seven tricyclic diamondoid acids. Most of the NAs modelled were predicted to have lethal median concentrations (LC50) > 100 μM for the three aquatic species modelled. Polycyclic acids containing a single aromatic ring were predicted to be the most toxic to fathead minnows with LC50s typically ca 1 μM. Some of these compounds were also predicted to be the most carcinogenic (based on rat and mouse models), possess human estrogenic and androgenic activity and potentially disrupt reproductive processes. Some aliphatic pentacyclic acids also were predicted to exhibit androgenic activity and, uniquely amongst the compounds tested, act as substrates for the cytochrome P450 enzyme CYP3A4. Consistent with the models' predictions for the tricyclic acids, no estrogenic or androgenic activity was detected by ER/AR CALUX®. Further experimental validation of the predictions should now be performed for the compounds highlighted by the models (e.g. priority should perhaps be focused on the polycyclic monoaromatic acids and the aliphatic pentacyclic acids). If shown to be accurate, these compounds can then be targeted for toxicity reduction remediation efforts. © 2012 Elsevier B.V. All rights reserved.

1. Introduction The extraction of oil from the huge reserves contained within the sands of northern Alberta, Canada, has proved highly controversial, not least due to the large volumes of contaminated waters produced by the extraction processes. Many studies have concluded that the ‘naphthenic acid’ (NA) fraction of these oil sands process-affected waters (OSPW) was mainly responsible for the observed toxicity (see review by Headley et al., 2009) although other potentially toxic organic compounds such as alkylated phenols have also been reported in OSPW (Hargesheimer et al., 1984). NAs are a complex mixture of saturated cyclic and noncyclic carboxylic acids having the general

Abbreviations: ALP, alkaline phosphatase; AR, androgen receptor; BCF, bioconcentration factor; CALUX, chemical activated luciferase gene expression; CYP, cytochrome P450; ER, estrogen receptor; GC × GC-ToF-MS, comprehensive two-dimensional gas chromatography × time-of-flight mass spectrometry; GGT, gamma glutamyl transpeptidase; IC50, inhibition concentration 50%; IGC50, inhibition of growth concentration 50%; LC50, lethal concentration 50%; LDH, lactate dehydrogenase; NA, naphthenic acid; OSPW, oil sands process-affected waters; SGOT, serum glutamic oxaloacetic transaminase; SGPT, serum glutamic pyruvate transaminase; TD50, tumorigenic dose rate for 50% of test animals. ⁎ Corresponding author. Tel.: + 44 1752 584730. E-mail address: [email protected] (A.G. Scarlett). 0048-9697/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.scitotenv.2012.02.064

formula of CnH2n + zO2, where n is the carbon number, and z is a negative even integer related to the number of rings in the molecule (Rogers et al., 2002) (e.g.: z = 0, no rings; z = −2, 1 ring; z = −4, 2 rings, etc.), and are extensively used in a wide range of industrial processes such as tyre manufacture (Clemente and Fedorak, 2005). Rather than simply a problem associated with the oil sands industry, NAs are likely to be widespread environmental contaminants. Until recently, the structures of individual NAs present in OSPW were unknown but a range of acids has now been identified in one OSPW sample (Rowland et al., 2011a,c,f,g) and has since been verified in additional OSPW samples (Rowland et al., 2012). The identification of these acids using comprehensive multi-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-ToF-MS) has, in part, started to address the call for “solid science” to underpin environmental monitoring and regulation (Schindler, 2010), and provide some of the missing data identified by Weinhold (2011). In addition, toxicity testing, using the Microtox™ Vibrio fischeri bioluminescence assay, of a few of the NAs found in the OSPW sample and also in a commercial NA preparation (Jones et al., 2011) has provided some indication of the potential risk posed by NAs. However, although the Microtox™ assay provides a good initial screening tool, it does not give information of specific modes of toxic action and may not identify risks posed to higher organisms including humans. One concern in

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particular is endocrine disruption arising from exposure to OSPW and oil platform produced waters (He et al., 2011; Thomas et al., 2009). Despite a large reduction in NAs reported in ozone-treated OSPW, estrogenicity was not attenuated in mammalian cell lines (He et al., 2011) suggesting that NAs were not responsible. However, this is not necessarily the case as ozonation may create new estrogenic steroidal compounds (Rowland et al., 2011d). The recent identification of steroidal structures present in an OSPW NA extract, one of which was predicted to affect ER and AR (Rowland et al., 2011d), has highlighted the need to consider additional toxicological pathways and modes of action. Several of the acids identified in OSPW and petroleum-derived commercial NAs had to be specially synthesised (Rowland et al., 2011a,b,c,f) and only small quantities were available for toxicity testing. Thorough testing of large numbers of chemicals using a battery of test endpoints and organisms requires larger amounts and is also very time consuming and expensive. An alternative approach is to use computer models to predict toxicity and potential disruption of key systems (Simon-Hettich et al., 2006) and to identify chemicals for prioritisation (Tebby et al., 2011). Further studies can then be focused on specific individual or groups of chemicals which have predicted effects. Environmental monitoring and clean-up operations can also be directed at those compounds predicted to be most likely to cause harm to the environment or pose a risk to human health. The ADMET predictor™ software (Simulations Plus Inc., Lancaster, CA) was chosen as it provides an array of models including physicochemical, biopharmaceutical, metabolite and toxicity, that takes into account the three-dimensional structure of the molecules. Toxicity models are included for several organisms at different trophic levels and a range of human toxicity endpoints. The structures of some NAs resemble those of some pharmaceuticals such as Ibuprofen and Ibufenac (Figs. 1S and 2S); it is therefore useful to make predictions for adverse effects on human liver and ADMET predictor™ provides an estimation of binary likelihood of causing elevation in five diagnostic liver enzymes. The ability to detoxify environmental contaminants is also critical; ADMET predictor™ provides prediction for inhibitory potency of chemicals for the five major CYP P450 enzymes. Models may never eliminate the need for toxicity testing, but they can reduce unnecessary testing and highlight compounds that may pose the greatest threats (Simon-Hettich et al., 2006; Tebby et al., 2011). In this study, the effects of 54 NAs, a number of which have been identified in OSPW or commercial preparations of NAs, plus others more tentatively identified (Rowland et al., 2011a,b,c,e,f,g) were predicted by ADMET predictor™ models for an array of environmental and human health endpoints. Both petroleum-derived NA preparations and OSPW have also been shown to contain alkylated phenols (Hargesheimer et al., 1984; West et al., 2011). These acidic compounds are potentially toxic and also provide a useful comparison to the NAs, so the predicted toxicities of six alkylphenols were also modelled. The resulting toxicity predictions are considered in terms of the threat posed by these groups of compounds to health. This research will enable future studies to focus toxicity reduction methods and technologies on those compounds posing the greatest threat to health. 2. Experimental Compounds were chosen for modelling based on those reported to be present in a commercial NA preparation and from a Canadian OSPW NA extraction (Rowland et al., 2011a,b,c,e,f,g). Six compounds from eight structural classes of NAs plus six alkylphenols were selected to cover the range of molecular weights and isomers of the same carbon number. The NAs included: straight chain, alicyclic and aromatic compounds with a range of z numbers from 0 to −14 (Table 1). The ADMET predictor™ software (Simulations Plus Inc., Lancaster, CA) uses chemical structures and experimental data to create the

QSAR models which are then used to predict properties of the molecules. The models provide a range of physicochemical outputs (e.g. log P and water solubility), as well as predictive toxicity to organisms including the ciliate Tetrahymena pyriformis (concentration of toxicant needed to inhibit 50% growth (IGC50) after ca 40 h exposure), the water flea Daphnia magna (48 h exposure lethality (LC50) and Fathead minnow Pimephales promelas (96 h exposure lethality (LC50). ADMET predictor™ gave a warning that the polycyclic monoaromatic acids were outside of the T. pyriformis model so these data should be treated with caution. Bioconcentration factors (BCF) for fish were also modelled. Predicted toxicity to a range of human systems is also provided. Binary likelihood of causing elevation in diagnostic liver enzymes: alkaline phosphatase (ALP), serum glutamic oxaloacetic transaminase (SGOT), serum glutamic pyruvate transaminase (SGPT), lactate dehydrogenase (LDH) and gamma glutamyl transpeptidase (GGT). Models are also provided for predicting carcinogenicity, mutagenic chromosomal aberrations, estrogenicity, androgenicity, and reproductive/ developmental toxicity. To better understand potential toxicity, knowledge of the specific metabolites resulting from metabolic transformations is often important. The five CYP enzymes modelled account for the majority of Phase I metabolic transformations of most environmental organic contaminants. The model classifies a chemical based on inhibition of five P450 enzymes (1A2, 2C19, 2C9, 2D6, and 3A4) and whether it is predicted to be a substrate for the CYPs. Inhibition of a CYP may increase the bioavailability of other chemicals. If a chemical is a substrate for a CYP, it may be metabolised and bioactivated into more active compounds. Inhibitory potency of compounds to key detoxifying enzymes is provided as Michaelis–Menten kinetic constants for hydroxylation reactions catalysed by the five P450 enzymes. Full details of the basis for models and validation of the training sets used are available online: http://www.simulations-plus.com/ Products.aspx?grpID=1&cID=11&pID=13 [accessed 24 October 2011]. A list of publications pertaining to the models is also available online: http://www.simulations-plus.com/Publication.aspx [accessed 07 February 2012]. For further independent validation of the P. promelas and D. magna LC50 predictions, we used a dataset for a group of parabens, importantly published (Dobbins et al., 2009) after the datasets used for the ADMET predictor™ model training sets. The parabens have some structural similarities to both NAs and phenols and so provided a reasonable test for the models. Linear regression analyses of measured LC50s with predicted values showed moderately strong relationships, r 2 = 0.72 (p = 0.03) and r 2 = 0.68 (p = 0.02) for P. promelas and D. magna endpoints respectively (Table 1S). Structural representations of each chemical were input into ADMET predictor™ as three-dimensional .sdf files. It was important to input the structures in this format as physicochemical and toxicity outputs, especially for cage structures, can be sensitive to spatial 3D configurations. Two-dimensional representations of the structures are provided in Fig. 1S. The default pH of 7.4 was used but does not have an effect on the models used for this study. The chemicals were grouped by structural classes (e.g. branched aliphatic acids, monoaromatic acids and so on). The groupings and coding used in graphs and tables are provided in Table 1. Because it is unlikely that the ADMET predictor™ models' training sets would have included cage structures similar to that of diamondoid acids, representatives of this type of NA (Table 2S) were experimentally tested using a panel of human cell-derived nuclear receptor reporter gene bioassays (CALUX® panel, Biodetection Systems, NL) for estrogenic (ER), androgen (AR), peroxisome-proliferation (PPAR), or aryl hydrocarbon (DR) receptor-mediated transactivation. Compounds were dissolved in DMSO to a stock concentration of 0.01 M and a dilution series prepared, after which exposure medium was prepared containing 0.1% DMSO (0.8% DMSO for DR CALUX). The cells were pre-incubated in 96-well plates for 24 hours at (37 C, 5% CO2) before medium was replaced with exposure medium. Cells were exposed for 24 hours,

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Table 1 Physical properties of chemicals tested. Code

Chemical

Formula

Mol wt

Mol vol

Solubility

(Dalton)

(cm− 3 mol− 1)

logP

g L− 1

za

idb OP OP OP OP OP OP

Aliphatic n-acids n-ali-1 n-decanoic n-ali-2 n-undecanoic n-ali-3 n-dodecanoic n-ali-4 n-tridecanoic n-ali-5 n-tetradecanoic n-ali-6 n-octadecanoic

C10H20O2 C11H22O2 C12H24O2 C13H26O2 C14H28O2 C18H36O2

172.3 186.3 200.3 214.4 228.4 284.5

224 245 266 287 308 392

3.91 4.41 4.91 5.40 5.89 7.77

1.37E − 01 6.14E − 02 2.90E − 02 1.53E − 02 8.52E − 03 1.45E − 03

0 0 0 0 0 0

Aliphatic branched acids br-ali_1 3,7-dimethyloctanoic br-ali_2 2,6-dimethylheptanoic br-ali_3 7-methyldecanoic br-ali_4 4-methyldodecanoic br-ali_5 2,6,10-trimethylundecanoic br-ali_6 13-methyltetradecanoic

C10H20O2 C9H18O2 C11H22O2 C13H26O2 C14H28O2 C15H30O2

172.3 158.2 186.3 214.4 228.4 242.4

224 203 245 287 308 329

3.57 3.22 4.22 5.24 5.45 6.17

7.72E − 01 1.15E + 00 2.24E − 01 3.55E − 02 3.86E − 02 6.45E − 03

0 0 0 0 0 0

Aliphatic cyclic acids cyc_1 3-cyclohexylpropanoic cyc_2 4-methylcyclohexylethanoic cyc_3 4-cyclohexylbutanoic cyc_4 4-ethylcyclohexylethanoic cyc_5 5-cyclohexylpentanoic cyc_6 4-n-propylcyclohexylethanoic

C9H16O2 C9H16O2 C10H18O2 C10H18O2 C11H20O2 C11H20O2

156.2 156.2 170.3 170.3 184.3 184.3

182 182 203 203 224 224

2.78 2.68 3.32 3.19 3.85 3.74

1.00E + 00 1.43E + 00 5.03E − 01 6.21E − 01 2.02E − 01 3.42E − 01

−2 −2 −2 −2 −2 −2

P P P P

Aliphatic bicyclic acids Bi_1 Bicyclo[4.3.0]nonane-2-carboxylic Bi_2 Bicyclo[4.3.0.]nonane-2-ethanoic Bi_3 3-methylbicyclo[3.3.0]octane-1- carboxylic Bi_4 Decahydronaphthalene-2-carboxylic Bi_5 Decahydronaphthalen-2-ylacetic Bi_6 3-(bicyclo[4.4.0]non-2′-yl)propanoic

C10H16O2 C11H18O2 C10H16O2 C11H18O2 C12H20O2 C13H22O2

168.2 182.3 168.2 182.3 196.3 210.3

182 203 182 203 224 245

2.78 3.19 2.68 3.20 3.61 4.13

7.88E − 01 3.22E − 01 1.00E + 00 5.38E − 01 2.72E − 01 9.52E − 02

−4 −4 −4 −4 −4 −4

P P P P P P

Aliphatic tricyclic acids tri_1 Adamantane-1-carboxylic tri_2 Adamantane-1-ethanoic tri_3 3-methyl-adamantane-1-ethanoic tri_4 3,5-dimethyladamantane-1-carboxylic tri_5 3-ethyladamantane-1-carboxylic tri_6 3,7-dimethyl-1-adamantane ethanoic

C11H16O2 C12H18O2 C13H20O2 C13H20O2 C13H20O2 C14H22O2

180.3 194.3 208.3 208.3 208.3 222.3

182 203 224 224 224 245

2.82 3.16 3.58 3.76 3.72 4.09

4.85E − 01 2.20E − 01 1.29E − 01 1.89E − 01 1.40E − 01 8.87E − 02

−6 −6 −6 −6 −6 −6

OP O O

Aliphatic tetra/pentacyclic acids te_1 Tetracyclo[7.3.1.06,11]tridecane-3-carboxylic te_2 3-methyltetracyclo[7.3.1.06,11] tridecane-3-carboxylic pe_1 Diamantane-1-carboxylic pe_2 Diamantane-3-carboxylic pe_3 Diamantane-4-carboxylic pe_4 3,4-dimethyl-diamantane-3-carboxylic

C14H20O2 C15H22O2 C15H20O2 C15H20O2 C15H20O2 C17H24O2

220.3 234.3 232.3 232.3 232.3 260.3

224 245 224 224 224 266

3.47 3.90 3.48 3.39 3.51 4.22

9.56E − 02 5.68E − 02 8.74E − 02 8.18E − 02 6.07E − 02 3.01E − 02

−8 −8 − 10 − 10 − 10 − 10

O O O O O

Monoaromatic acids (1) M-aro_1 4-methylphenylethanoic M-aro_2 3,5-dimethylbenzoic M-aro_3 3-phenylpropanoic M-aro_4 p-ethylbenzoic M-aro_5 4-ethylphenylethanoic M-aro_6 3,4,5-trimethylbenzoic

C9H10O2 C9H10O2 C9H10O2 C9H10O2 C10H12O2 C10H12O2

150.2 150.2 150.2 150.2 164.2 164.2

140 140 140 140 161 161

1.97 2.69 1.90 2.83 2.44 3.14

1.93E + 00 5.20E − 01 2.38E + 00 3.39E − 01 7.88E − 01 2.38E − 01

−8 −8 −8 −8 −8 −8

Monoaromatic acids (2) M-aro_7 4-isopropylbenzoic M-aro_8 4-i-propylphenylethanoic M-aro_9 4-phenylpentanoic M-aro_10 3-methyl-5-phenylhexanoic M-aro_11 4-(3,5-dimethylphenyl)butanoic M-aro_12 4-(3,5-dimethylphenyl)pentanoic

C10H12O2 C11H14O2 C11H14O2 C12H16O2 C12H16O2 C13H18O2

164.2 178.2 178.2 192.3 192.3 206.3

161 182 182 203 203 224

3.15 2.79 2.63 3.12 3.23 3.56

2.86E − 01 3.81E − 01 4.89E − 01 3.21E − 01 2.05E − 01 1.47E − 01

−8 −8 −8 −8 −8 −8

P P P

Polycyclic monoaromatic acidsc PMaro_1 Polycyclic monoaromatic PMaro_2 Polycyclic monoaromatic PMaro_3 Polycyclic monoaromatic PMaro_4 Polycyclic monoaromatic PMaro_5 Polycyclic monoaromatic PMaro_6 Polycyclic monoaromatic

C20H26O3 C19H24O3 C20H28O3 C19H26O2 C21H28O3 C20H28O2

314.4 300.4 316.4 286.4 328.4 300.4

315 294 336 308 336 329

3.14 2.85 4.45 5.54 3.57 6.00

5.54E − 02 7.67E − 02 3.94E − 02 8.39E − 03 5.46E − 02 7.84E − 03

− 14 − 14 − 12 − 12 − 14 − 12

O O O O O O

1 2 3 4 5 6

P

P OP

O

P P P P P

P P

(continued on next page)

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Table 1 (continued) Code

Chemical

Non acids — alkylphenols PhOH_1 2-isopropylphenol PhOH_2 4-isopropylphenol PhOH_3 2,3-dihydro-1H-inden-4-ol PhOH_4 3,4,5-trimethylphenol PhOH_5 3,5-diethylphenol PhOH_6 4-cyclopentylphenol a b c

Formula

C9H12O C9H12O C9H10O C9H12O C10H14O C12H16O

Mol wt

Mol vol

Solubility

(Dalton)

(cm− 3 mol− 1)

logP

g L− 1

za

136.2 136.2 134.2 136.2 150.2 176.3

147 147 126 147 168 189

2.75 2.79 2.60 2.74 3.28 4.07

2.63E + 00 2.28E + 00 1.18E + 00 1.33E + 00 6.85E − 01 1.10E − 01

na na na na na na

idb

P P P P

z is a negative integer in the formula CnH2n + zO2. id indicates that a chemical has been identified in oil sands process-affected waters (O) or in a commercial preparation of petrogenic naphthenic acids (P). Compound names too long for table; chemical structures and names are provided in the Supplementary material, Fig. 1. Structural identification tentative.

after which cells were washed, lysed and luminescence was analysed in a luminometer after addition of luciferine as substrate. 3. Results 3.1. Environmental toxicity The toxicity to environmental receptor organisms was predicted for three aquatic species at different trophic levels. Two of these were lethal endpoints: P. promelas and D. magna, and one sublethal endpoint: growth inhibition of T. pyriformis. Generally the three species were predicted to have similar sensitivities to the compounds with endpoints typically within an order of magnitude (Fig. 1). Overall, there was a general tendency within groups for increasing toxicity with increasing carbon number and predicted log P (Fig. 1; Table 1). For the straight chain aliphatic naphthenic acids (n-ali), P. promelas was predicted to be affected the most with the highest molecular weight, n-octadecanoic (n-ali_6), predicted to have a 96 h LC50 of 0.56 μM; (Fig. 1). The C14 n-tetradecanoic acid was predicted to produce a P. promelas 96 h LC50 of 5.4 μM (Fig. 1) but the corresponding C14 branched NAs (br-ali_5) was predicted to be less toxic, (P. promelas 96 h LC50, 36.8 μM), and this reduction in predicted toxicity for branched aliphatic structures was generally the case for all species (Fig. 1). The monocyclic NAs (cyc) and bicyclic NAs (bi) were predicted to be less toxic than the straight chain and branched acids of equivalent molecular weight (Fig. 1; Table 1). In contrast, Jones et al. (2011) reported decalin-2-propanoic to be relatively toxic to V. fischeri. Compared to the acyclic acids, the tri-, tetra- and pentacyclic acids were predicted by the models to have relatively low toxicity towards the three species (Fig. 1). The monoaromatic NAs (m-aro) were also predicted to be of lower environmental toxicity than the acyclic acids but, in contrast to the aliphatic NAs, D. magna was predicted to be the most sensitive species (Fig. 1). The polycyclic monoaromatic NAs (PMaro), i.e. containing a single aromatic and two fused alicyclic rings, were predicted to have similar toxicities to n-octadecanoic for all species. The predicted toxicities of the phenols were in the same range as the NAs tested. Predicted fish BCFs were generally low, typically b10 as would be expected for NAs (Fig. 1). The alkylphenols were predicted to have a slightly greater tendency to bioaccumulate (Fig. 1). 3.2. Human liver toxicity All of the chemicals tested were predicted to disrupt at least one of the liver enzymes (Table 2). SGOT (also known as aspartate transaminase) was predicted to be affected by all NAs but not alkylphenols (Table 2). The enzyme LDH was predicted to be affected by most NAs, the exceptions being those containing an aromatic ring which generally did not elicit a response. Of the alkylphenols only the isopropylphenols were predicted to disrupt LDH (Table 2). Most of the

cyclic NAs, including all the tetra and pentacyclic acids, were predicted to disrupt ALP but otherwise there was no clear pattern; none of the straight chain aliphatic acids and only a couple of the aromatic acids were predicted to affect ALP (Table 2). All of the alkylphenols were predicted to affect GGT but, with one exception, none of the NAs. SGPT (also known as alanine transaminase) is the only enzyme specific to the liver (Prati et al., 2002) and this was predicted to be unaffected by nearly all the chemicals (Table 2). 3.3. Endocrine disruption and reproduction Two of the polycyclic monoaromatic acids were predicted to affect ER, as were most of alkylphenols (Table 2). AR was predicted to be affected by half of the tetracyclic and pentacyclic acids tested (Table 2). Of the latter, the structures predicted to affect the AR had the carboxylic acid group substituted on the 3 position (Table 2, Fig. 1S). Of the NAs, only n-octadecanoic acid, two of the tricyclic diamondoid acids and three of the polycyclic monoaromatic acids were predicted to disrupt reproductive development (Table 2). Results of the CALUX® panel of assays indicated that there was no activity across any of the tested endpoints, and it was not possible to calculate either IC50 or IC20 values. There was no measurable steroidreceptor activation in any of the adamantane acids at any of the tested concentrations. Similarly, no effect was observed for the PPAR or DR assays. 3.4. Carcinogenicity and mutagenicity The potential for chemicals to induce tumours is calculated by ADMET predictor™ based on both rat and mouse models. The predicted carcinogenicity TD50 values for the rat model were above 50 mg kg − 1 d − 1 for most chemicals tested and for the mouse model, most TD50s were above 100 mg kg − 1 d − 1 (Fig. 3S). Chemicals containing an aromatic ring were predicted to be relatively more carcinogenic with rat TD50s in the range 19–85 mg kg − 1 d − 1. None of the chemicals tested were predicted to be mutagenic in any of the 10 Ames test models based on Salmonella typhimurium (data not shown). 3.5. Cytochrome P450 enzymes In general, the alkylphenols were substrates for more of the CYPs than the NAs (Supplementary material, Table 2). Nearly all the chemicals tested were predicted to be a substrate for CYP2C9, the only exceptions being n-tetradecanoic acid and n-octadecanoic acid (Table 3S). Many of the chemicals also were predicted to inhibit CYP2C9, the notable exceptions being nearly all of the aliphatic multicyclic acids and the alkylphenols (Table 3S). Most of the monoaromatic acids and the alkylphenols were predicted to act as a substrate for CYP1A2. With the exception of one of the alkylphenols (2,3-

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Fig. 1. Predicted 96 h LC50 for P. promelas, ca 40 h IGC50 for T. pyriformis and 48 h LC50 for D. magna expressed as − log mM, and bioconcentration factors for fish.

dihydro-1H-inden-4-ol), none of the compounds were predicted to inhibit CYP1A2. The enzyme CYP2D6 was generally predicted to be unaffected by the compounds investigated and there was little apparent commonality to the predictions for CYP2C19 although a number

of the monoaromatic acids were predicted to act as a substrate and inhibit this enzyme (Table 3S). All the pentacyclic acids were predicted to be a substrate for CYP3A4; the only other NA to do so was the highest molecular weight (C21) polycyclic monoaromatic acid.

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Table 2 Predicted effect (filled circles) of compounds on human liver enzymes, endocrine system and reproductive processes. Compound names are provided in Table 1. Liver enzymes

Endocrine/ reproduction LDH

SGOT

SGPT

ERa

ARa

Reprob

○ ○ ○ ○ ○ ○

● ● ● ● ● ●

● ● ● ● ● ●

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ●

Aliphatic branched acids br-ali_1 ○ ○ br-ali_2 ● ○ br-ali_3 ○ ○ br-ali_4 ● ○ br-ali_5 ○ ○ br-ali_6 ○ ○

● ● ● ● ● ●

● ● ● ● ● ●

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

Aliphatic cyclic acids cyc-1 ● cyc_2 ● cyc_3 ● cyc_4 ● cyc_5 ● cyc_6 ●

○ ○ ○ ○ ○ ○

● ● ● ● ● ●

● ● ● ● ● ●

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

Aliphatic bicyclic acids bi_1 ● ○ bi_2 ○ ○ bi_3 ● ○ bi_4 ● ○ bi_5 ● ○ bi_6 ● ○

● ● ● ● ● ●

● ● ● ● ● ●

● ○ U ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

Aliphatic tricyclic acids tri_1 ● ○ tri_2 ○ ○ tri_3 ○ ○ tri_4 ● ○ tri_5 ● ○ tri_6 ○ ○

● ● ● ● ● ●

● ● ● ● ● ●

U ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ● ○ ○ ●

Aliphatic tetra/pentacyclics te_1 ● ○ te_2 ● ○ pe_1 ● ○ pe_2 ● ○ pe_3 ● ○ pe_4 ● ○

● ● ● ● ● ●

● ● ● ● ● ●

○ U ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ● ○ ● ○ ●

○ ○ ○ ○ ○ ○

Monoaromatic acids (1) M-aro_1 ○ ○ M-aro_2 ○ ○ M-aro_3 ● ● M-aro_4 ○ ○ M-aro_5 ○ ○ M-aro_6 ● ○

● ○ ● ● ○ ○

● ● ● ● ● ●

○ ● ○ ● ○ ●

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

Monoaromatic acids (2) M-aro_7 ○ ○ M-aro_8 ○ ○ M-aro_9 ○ ○ M-aro_10 ○ ○ M-aro_11 ○ ○ M-aro_12 ○ ○

○ ○ ● ○ ○ ○

● ● ● ● ● ●

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

Polycyclic monoaromatic acids PMaro_1 ○ ○ PMaro_2 ○ ○ PMaro_3 ○ ○ PMaro_4 ○ ○ PMaro_5 ○ ○ PMaro_6 ○ ○

○ ○ ○ ○ ○ ○

● ● ● ● ● ●

○ ○ ○ ○ ○ ○

● ○ ○ ○ ● ○

● ● ○ ○ ● ●

● ● ○ ○ ● ○

ALP

Aliphatic n- acids n-ali-1 ○ n-ali-2 ○ n-ali-3 ○ n-ali-4 ○ n-ali-5 ○ n-ali-6 ○

Liver enzymes Code

GGT

Code

Table 2 (continued)

ALP

GGT

Non-acids alkylphenols PhOH_1 ○ ● PhOH_2 ○ ● PhOH_3 ○ ● PhOH_4 ○ ● PhOH_5 ○ ● PhOH_6 ○ ●

Endocrine/ reproduction LDH

SGOT

SGPT

ERa

ARa

Reprob

● ● ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ○ ○ ○ ○ ○

○ ● ○ ● ● ●

● ● ● ● ● ●

○ ○ ● ○ ○ ○

a

Detectable binding to the estrogen receptor (ER) or androgen receptor (AR). Disruption to the reproductive process of organisms, including adverse effects to sexual organs, behavior, ease of conception, and developmental toxicity of offspring both before and after birth (Repro). b

4. Discussion 4.1. Environmental toxicity Numerous straight chain NAs (z = 0) have previously been identified within a commercial NA preparation (Rowland et al., 2011e) and within multiple OSPW samples (Rowland et al., 2012). Frank et al. (2009) reported D. magna 48 h LC50 values of 1.3 mM ( ± 0.4 mM) for n-decanoic acid and 0.59 (± 0.20 mM) for cyclohexylpentanoic acid. The modelled predictive values for these chemicals were 0.11 mM and 0.21 mM respectively. Decanoic acid was reported to produce a T. pyriformis IGC50 of 0.31 mM (Seward and Schultz, 1999); the predicted IGC50 was 0.17 mM. These comparisons suggest a reasonable accuracy of models' predictions. Monocyclic acids (z = − 2) would appear not to be abundant in OSPW (Martin et al., 2008) but have been reported in petroleum derived NAs (Rowland et al., 2011e). Bicyclic NAs (z = −4) of unknown structures are reported to be major components of OSPW (Martin et al., 2008) and tricyclic (tri; z = −6), tetracyclic (te; z = − 8) and pentacyclic (pe; z = − 10) acids, some with known structures, were reported to be common in an OSPW sample (Rowland et al., 2011a, c,g). Most of the cyclic compounds were predicted to have LC50 or IGC50 concentrations greater than 0.1 mM. The pentacyclic acids were predicted to be relatively the most toxic but this may simply be related to their molecular size (Table 1) rather than structure (Fig. 1S). Similarly, the predicted toxicity of the aromatic acids may be related to molecular size as the low molecular weight monocyclic aromatic acids were predicted to have LC50 or IGC50 concentrations typically greater than 0.1 mM (Fig. 1). Alkylated phenols are minor constituents within some-petroleum derived preparations and the possibility that toxicity attributed previously to NAs may, in part, in fact be due to these chemicals has been expressed (West et al., 2011). Although also present within OSPW, alkylphenols may not have been extracted into the NA fraction by the method used by Frank et al. (2006) and hence not have been detected by GC × GC-ToF-MS. Devillers (1988) reported a D. magna 24 h IC50 (immobilisation) of 0.14 mM for 2,3,6- trimethylphenol and 0.20 mM for the 2,3,5 and 2,4,6 isomers. The model predicted a D. magna 48 h LC50 value of 0.06 mM for 3,4,5-trimethylphenol (PhOH_4) and all alkylphenols tested to be in the range ca 0.009– 0.078 mM (Fig. 1). Choi et al. (2004) reported P. promelas 96 h LC50 values in the range 0.04–0.1 mM for the three isomers of isopropylphenol with the 4-iso structure being the most toxic. The predicted toxicities for these chemicals were 0.12–0.14 mM with the 4-iso structure predicted to the most toxic. Of the NAs tested, the polycyclic monoaromatic compounds likely pose the greatest threat to environmental species, especially fish, as these were predicted to be among the most toxic with P. promelas LC50 values in the range 0.3–2 μM and a couple of the compounds were predicted to have a greater tendency to bioaccumulate (Fig. 1).

A.G. Scarlett et al. / Science of the Total Environment 425 (2012) 119–127

4.2. Human liver toxicity Some of the NA structures resemble some pharmaceuticals in structure. For example, the nonsteroidal anti-inflammatory drugs Ibuprofen ((RS)-2-(4-(2-methylpropyl)phenyl)propanoic acid) and Ibufenac (4-(2-methylpropyl)-benzeneacetic acid) have somewhat similar structures to some aromatic naphthenic acids identified in a commercial preparation (Fig. 2S). Ibufenac was withdrawn from use due, in part, to concerns regarding liver toxicity (Bessone, 2010). It was therefore surprising that the structurally similar monoaromatic acids (z = −8), and the polycyclic monoaromatic acids (z = −12 and z = −14), were predicted to be two of the groups of chemicals least likely to cause an effect on liver enzymes, with only SGOT predicted to be affected by all aromatic NAs and only a few aromatic acids predicted to disrupt other liver enzymes. However, only elevated SGOT was reported in patients taking Ibufenac (Hart and Boardman, 1965) and for both Ibuprofen and Ibufenac the model predicted only SGOT to be affected (data not shown). The compounds predicted to affect the most liver enzymes were the aliphatic cyclic NAs which typically were predicted to disrupt three of the five enzymes (Table 2). Derivatives of the tricyclic adamantanes have been used in medicine for the treatment of Parkinson's disease and as antivirals (Maugh, 1979). The pentacyclic diamantane structure has been shown to strongly bind to liver microsomes from phenobarbitaltreated rats and metabolic studies show that the microsomes readily metabolize diamantane to mono-, di- and possibly tri-hydroxy derivatives (Hodek et al., 1988). 4.3. Endocrine disruption and reproduction Petrogenic naphthenic acids of unknown structures have been reported to be weak ER agonists but, due to their high abundance, may account for much of the 65% of the “unknown” ER agonist potency in North Sea UK produced waters while also disrupting the binding of AR agonists to the AR ligand receptor (Thomas et al., 2009). Some of the tetracyclic and pentacyclic acids were predicted to affect AR but not ER (Table 2). A number of tricyclic adamantane acids were commercially available and therefore it was possible to test for endocrine disruption activity using ER and AR CALUX®. The unusual structure of the diamondoid acids raised the possibility of false negative results derived from the models so it was therefore important to test representative compounds experimentally. The results of no activity were consistent with the model predictions, although two of the tricyclic compounds tested were predicted by models to affect reproductive development (Table 2). The diamondoid structures predicted to affect AR had the carboxylic acid group substituted on the 3 position (Table 2, Fig. 1S) but this could be coincidental. Several of the polycyclic monoaromatic acids were predicted to affect ER, AR and reproduction (Table 2). Such NAs are z ≥ 8 (four or more double bond equivalents) species with structures similar to some steroidal chemicals (Fig. 1S); therefore potential hormonal activity was perhaps not unexpected. However, hormonal activity is very dependent on structure. For example, acids related to estradiol are not estrogenic but many esters of the latter are potent estrogens (Labaree et al., 2003). The identification of some of the structures within OSPW is currently tentative so it will be important to confirm the structures so that they can be tested for ER and AR activity using suitable bioassays. 4.4. Carcinogenicity and mutagenicity Despite reports of a high number of cases of a rare form of bile duct cancer (cholangiocarcinoma) reported in residents of Fort Chipewyan, located approximately 600 km north-east of Edmonton, Alberta, Canada, which had prompted concerns regarding the oil sands industry, a report commissioned by the Alberta Cancer Board

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(2009) concluded that there was no evidence supporting an abnormal rate of cholangiocarcinoma, but there was a higher than expected number of general cancers. Of the NAs tested, the tentatively identified polycyclic monoaromatic acids were predicted to have rat TD50s b 34 mg kg− 1 d − 1 (Fig. 3S). For comparison, the diaromatic hydrocarbon naphthalene was reported to produce a most toxic TD50 value of 22 mg kg− 1 d − 1 (CPDB, 2010). For naphthalene, the ADMET predictor™ models predicted a value of 192 mg kg− 1 d− 1 (data not shown). 4.5. Cytochrome P450 enzymes The CYP1 enzymes are responsible for both metabolically activating and detoxifying aromatic hydrocarbons (Nebert et al., 2004) so it was expected that the aromatic structures would act as a substrate for CYP1A2. Although this was the case for the monocyclic structures, the model did not predict the polycyclic acids with a single aromatic ring to interact with this enzyme. The prediction that all of the pentacyclic acids were a substrate for CYP3A4 was interesting. CYP3A4 is present in the largest quantity of all the CYPs in the liver (Wilkinson, 1996) and, although the pentacyclic acids were predicted to affect three of the five liver enzymes, this was also the prediction for most of the aliphatic cyclic acids. 4.6. Implications for oil sands and oil refinery and other industries producing or using NAs Although most of the concerns about NA toxicity have been focused on the oils sands industry, waste waters from other oil extraction and refining industries contain NAs and they are used in a wide range of manufacturing processes (see review by Clemente and Fedorak, 2005). These compounds may therefore be common environmental contaminants but would not be routinely monitored. Until recently the identity of individual NA structures within OSPW and commercial NA preparations were largely unknown. Now that a considerable number of compounds have been identified within a range of structural classes (Rowland et al., 2011a,c,e,f,g) it has been possible to screen them for baseline toxicity using a microbial assay (Jones et al., 2011) and make predictions for a range of environmental and human toxic endpoints reported herein. Recent research has focused upon how to reduce the toxicity of NAs, such as by oxidation techniques, bioremediation and adsorption methods (e.g. He et al., 2011; Johnson et al., 2011; Martin et al., 2010; Pourrezaei et al., 2011). Knowing what structures are present and which are most likely to impact the environment or pose a threat to human health, allows research to be targeted at specific compounds or groups of compounds. Similarly, environmental monitoring can be focused on specific groups. Tailings pond waters from the oil sands industry are known to be toxic to fish (Clemente and Fedorak, 2005) and Lai et al. (1996) reported that some tailing pond waters caused up to 100% mortality to P. promelas although how much of this was attributable to NAs was unknown. Of the NA structures input into the model, the polycyclic monoaromatic acids were predicted to be the most toxic to P. promelas with LC50 values of about 1 μM; this was typically over two orders of magnitude more toxic than many of the other NAs (Fig. 1). Hence, even if only present at low relatively low concentrations within the environment, such compounds could have effects. Kavanagh et al. (2011) reported that OSPW containing >25 mg L − 1 NAs completely inhibited spawning of P. promelas and reduced male secondary sexual characteristics. The authors further reported that males had lower concentrations of testosterone and 11-ketotestosterone whereas females had lower concentrations of 17β-estradiol. Again, of the NA structures tested, the polycyclic monoaromatic acids were predicted herein to most affect human ER, AR and reproductive development (Table 2). In addition, these compounds were also predicted to be the most carcinogenic (Fig. 3S). Therefore the potential for bioremediation or alternative clean-

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up measures for these types of compounds should perhaps be investigated. The pentacyclic acids were predicted to disrupt liver function and were predicted to be substrates for several CYPs including CYP3A4, which is a major detoxifying enzyme within the human liver. If these compounds can be altered, such as by ring opening, it will be important to test how this affects their toxicity. 5. Conclusions By modelling the toxicities of a broad range of NAs, present within OSPW or petroleum-derived commercial preparations, it has been possible to identify compounds that potentially could be most harmful to aquatic species and human health. Of all the classes of compounds modelled, the tentatively identified polycyclic monoaromatic acids appear to pose the greatest concern for both the aquatic environment and humans. These compounds were predicted to be relatively toxic to P. promelas and some were more likely to bioaccumulate. Some were also predicted to have estrogenic, androgenic and reproductive development affects, and were relatively the most carcinogenic compounds. A second class of compound that deserves further study is the pentacyclic acids due to their unusual structures, predicted AR activity and substrates for CYP3A4. Priority should probably now be focused upon validating the predicted toxicities and activities of the polycyclic monoaromatic acids and the pentacyclic acids. If confirmed, research can then be directed towards toxicity reduction techniques. Supporting information available Supplementary information available consists of chemical structures of the compounds stated in Table 1 plus those of the pharmaceuticals Ibufenac and Ibuprofen. Predicted TD50 values for the chemicals administered to rats and mice, both predicted and measured LC50 values for the effect of parabens on P. promelas and D. magna, and prediction of likely sites of metabolic attack for human CYP enzymes 1A2, 2C19, 2C9, 2D6, and 3A4. Acknowledgements Research described in this paper was supported in part by an award from the European Research Council (award no. 228149). We thank Simulations Plus Inc., Lancaster, CA for use of a gratis copy of ADMET predictor™ software and Dr Michael S. Lawless for his advice concerning the models. We also thank Dr H Besselink of Biodetection Systems, NL for help and support in performing the CALUX® assay measurements. Appendix A. Supplementary data Supplementary data to this article can be found online at doi:10. 1016/j.scitotenv.2012.02.064. References ACB. Alberta Cancer Board Division of Population Health and Information Surveillance. Cancer incidence in Fort Chipewyan, Alberta 1995–2006; 2009. Bessone F. Non-steroidal anti-inflammatory drugs: what is the actual risk of liver damage? World J Gastroenterol 2010;16:5651–61. Choi KH, Sweet LI, Meier PG, Kim PG. Aquatic toxicity of four alkylphenols (3-tertbutylphenol, 2-isopropylphenol, 3-isopropylphenol, and 4-isopropylphenol) and their binary mixtures to microbes, invertebrates, and fish. Environ Toxicol 2004;19:45–50. Clemente JS, Fedorak PM. A review of the occurrence, analyses, toxicity, and biodegradation of naphthenic acids. Chemosphere 2005;60:585–600. CPDB. The Carcinogenic Potency Database. . Available: http://potency.berkeley.edu/ cpdb.html2010. [Accessed 29th August 2011]. Devillers J. Acute toxicity of cresols, xylenols, and trimethylphenols to Daphnia-magna Straus-1820. Sci Total Environ 1988;76:79–83.

Dobbins LL, Usenko S, Brain RA, Brooks BW. Probabilistic ecological hazard assessment of parabens using Daphnia magna and Pimephales promelas. Environ Toxicol Chem 2009;28:2744–53. Frank RA, Kavanagh R, Burnison BK, Headley JV, Peru KM, Van Der Kraak G, et al. Diethylaminoethyl-cellulose clean-up of a large volume naphthenic acid extract. Chemosphere 2006;64:1346–52. Frank RA, Fischer K, Kavanagh R, Burnison BK, Arsenault G, Headley JV, et al. Effect of carboxylic acid content on the acute toxicity of oil sands naphthenic acids. Environ Sci Technol 2009;43:266–71. Hargesheimer EE, Coutts RT, Mackinnon MD. Characterization of simple phenols in oil sands extraction-process water. Environ Technol Lett 1984;5:433–40. Hart DF, Boardman PL. Ibufenac (4-isobutylphenyl acetic acid). Ann Rheum Dis 1965;24:61–5. He YH, Wiseman SB, Hecker M, Zhang XW, Wang N, Perez LA, et al. Effect of ozonation on the estrogenicity and androgenicity of oil sands process-affected water. Environ Sci Technol 2011;45:6268–74. Headley JV, Peru KM, Barrow MP. Mass spectrometric characterization of naphthenic acids in environmental samples: a review. Mass Spectrom Rev 2009;28:121–34. Hodek P, Janscak P, Anzenbacher P, Burkhard J, Janku J, Vodicka L. Metabolism of diamantane by rat-liver microsomal cytochromes-P-450. Xenobiotica 1988;18: 1109–18. Johnson RJ, Smith BE, Sutton PA, McGenity TJ, Rowland SJ, Whitby C. Microbial biodegradation of aromatic alkanoic naphthenic acids is affected by the degree of alkyl side chain branching. ISME J 2011;5:486–96. Jones D, Scarlett AG, West CE, Rowland SJ. The toxicity of individual naphthenic acids to Vibrio fischeri. Environ Sci Technol 2011;45:9776–82. Kavanagh RJ, Frank RA, Oakes KD, Servos MR, Young RF, Fedorak PM, et al. Fathead minnow (Pimephales promelas) reproduction is impaired in aged oil sands process-affected waters. Aquat Toxicol 2011;101:214–20. Labaree DC, Zhang JX, Harris HA, O'Connor C, Reynolds TY, Hochberg RB. Synthesis and evaluation of B-, C-, and D-ring-substituted estradiol carboxylic acid esters as locally active estrogens. J Med Chem 2003;46:1886–904. Lai JWS, Pinto LJ, Kiehlmann E, BendellYoung LI, Moore MM. Factors that affect the degradation of naphthenic acids in oil sands wastewater by indigenous microbial communities. Environ Toxicol Chem 1996;15:1482–91. Martin JW, Han XM, Peru KM, Headley JV. Comparison of high- and lowresolution electrospray ionization mass spectrometry for the analysis of naphthenic acid mixtures in oil sands process water. Rapid Commun Mass Spectrom 2008;22:1919–24. Martin JW, Barri T, Han XM, Fedorak PM, El-Din MG, Perez L, et al. Ozonation of oil sands process-affected water accelerates microbial bioremediation. Environ Sci Technol 2010;44:8350–6. Maugh TH. Panel urges wide use of anti-viral drug. Science 1979;206:1058–60. Nebert DW, Dalton TP, Okey AB, Gonzalez FJ. Role of aryl hydrocarbon receptormediated induction of the CYP1 enzymes in environmental toxicity and cancer. J Biol Chem 2004;279:23847–50. Pourrezaei P, Drzewicz P, Wang Y, Gamal El-Din M, Perez-Estrada LA, Martin JW, et al. The impact of metallic coagulants on the removal of organic compounds from oil sands process-affected water. Environ Sci Technol 2011;45:7951–8596. Prati D, Taioli E, Zanella A, Della Torre E, Butelli S, Del Vecchio E, et al. Updated definitions of healthy ranges for serum alanine aminotransferase levels. Ann Intern Med 2002;137:1–9. Rogers VV, Liber K, MacKinnon MD. Isolation and characterization of naphthenic acids from Athabasca oil sands tailings pond water. Chemosphere 2002;48:519–27. Rowland SJ, Clough R, West CE, Scarlett AG, Jones D, Thompson S. Synthesis and mass spectrometry of some tri-and tetracyclic naphthenic acids. Rapid Commun Mass Spectrom 2011a;25:2573–8. Rowland SJ, Jones D, Scarlett AG, West CE, Hin LP, Boberek M, et al. Synthesis and toxicity of some metabolites of the microbial degradation of synthetic naphthenic acids. Sci Total Environ 2011b;409:2936–41. Rowland SJ, Scarlett A, West C, Jones D, Frank R. Diamonds in the rough: identification of individual naphthenic acids in oil sands process water. Environ Sci Technol 2011c;45:3154–9. Rowland SJ, West CE, Jones D, Scarlett AG, Frank RA, Hewitt LM. Steroidal aromatic ‘naphthenic acids’ in oil sands process-affected water: structural comparisons with environmental estrogens. Environ Sci Technol 2011d;45:9806–15. Rowland SJ, West CE, Scarlett AG, Jones D. Identification of individual acids in a commercial sample of naphthenic acids from petroleum by two-dimensional comprehensive gas chromatography/mass spectrometry. Rapid Commun Mass Spectrom 2011e;25:1741–51. Rowland SJ, West CE, Scarlett AG, Jones D, Boberek M, Pan I, et al. Monocyclic and monoaromatic naphthenic acids: synthesis and characterisation. Environ Chem Lett 2011f;9:525–33. Rowland SJ, West CE, Scarlett AG, Jones D, Frank RA. Identification of individual tetraand pentacyclic naphthenic acids in oil sands process water by comprehensive two-dimensional gas chromatography/mass spectrometry. Rapid Commun Mass Spectrom 2011g;25:1198–204. Rowland SJ, West CE, Scarlett AG, Ho C, Jones D. Differentiation of two industrial oil sands process-affected waters by two-dimensional gas chromatography/mass spectrometry of diamondoid acid profiles. Rapid Commun Mass Spectrom 2012;26:572–6. Schindler D. Tar sands need solid science. Nature 2010;468:499–501. Seward JR, Schultz TW. QSAR analyses of the toxicity of aliphatic carboxylic acids and salts to Tetrahymena pyriformis. SAR QSAR Environ Res 1999;10:557–67. Simon-Hettich B, Rothfuss A, Steger-Hartmann T. Use of computer-assisted prediction of toxic effects of chemical substances. Toxicology 2006;224:156–62.

A.G. Scarlett et al. / Science of the Total Environment 425 (2012) 119–127 Tebby C, Mombelli E, Pandard P, Pery ARR. Exploring an ecotoxicity database with the OECD (Q)SAR Toolbox and DRAGON descriptors in order to prioritise testing on algae, daphnids, and fish. Sci Total Environ 2011;409:3334–43. Thomas KV, Langford K, Petersen K, Smith AJ, Tollefsen KE. Effect-Directed Identification of Naphthenic Acids As Important in Vitro Xeno-Estrogens and Anti-Androgens in North Sea Offshore Produced Water Discharges. Environ Sci Technol 2009;43: 8066–71. Weinhold B. Alberta's oil sands: hard evidence, missing data, new promises. Environ Health Perspect 2011;119.

127

West CE, Jones D, Scarlett AG, Rowland SJ. Compositional heterogeneity may limit the usefulness of some commercial naphthenic acids for toxicity assays. Sci Total Environ 2011;409:4125–31. Wilkinson GR. Cytochrome P4503A (CYP3A) metabolism: prediction of in vivo activity in humans. J Pharmacokinet Biopharm 1996;24:475–90.