Supporting information to the manuscript. organism recovery

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1 Supporting information to the manuscript Toxicokinetic and toxicodynamic modeling explains carry-over toxicity from exposure to diazinon by slow organism recovery Roman Ashauer*, Anita Hintermeister, Ivo Caravatti, Andreas Kretschmann, Beate I Escher Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland The University of Queensland, National Research Centre for Environmental Toxicology (Entox), 39 Kessels Rd, Brisbane, Qld 4108, Australia * Corresponding author; phone: ; fax: ; roman.ashauer@eawag.ch -S1 -

2 Contents of supporting information Experimental methods...3 Organisms... 3 Toxicokinetic experiment... 4 Pulse toxicity experiment... 4 Chemicals... 6 Acute toxicity test... 7 Sample processing and analytical methods... 8 Data analysis and modeling Toxicokinetic-toxicodynamic model Parameter estimation Results and discussion Toxicokinetic experiment Carry-over toxicity Toxicokinetic-toxicodynamic parameters and model fit Concentrations in the water phase used as input for modeling References used in the supporting information S2 -

3 Experimental methods Organisms The freshwater invertebrate Gammarus pulex plays a major role in detritus processing in European streams and has been frequently used in toxicity testing or biomonitoring studies [1-3]. Since Gammarus pulex live up to approximately two years they are likely subject to repeated exposure to pollutants in the field and are ideally suited to study toxicokinetics and the time-course of effects experimentally. Gammarus pulex were collected from a small headwater stream ca. 20 km southeast of Zürich, Switzerland (Itziker Ried, E , N ) and acclimatized for 4 and 5 days before the experiments in conditions similar to the experiments. Experiments were carried out in artificial pondwater (APW, [4]). APW was aerated before use. Organisms were fed ad libitum with horse-chestnut leaf discs (diameter 20 mm) inoculated with Cladosporium herbarum [4]. Experiments were carried out at 13 C and 12:12h light:dark conditions. Dissolved oxygen, ph and conductivity were measured frequently. Table S1: Test organisms. Experiment Toxicokinetic experiment Pulse toxicity experiment Collection of Gammarus pulex Duration of Experiment Average mass of Gammarus pulex Approximate age of Gammarus pulex date dates mg days 12 Feb Feb a 194 b 6 Nov Nov - 2 Dec 2008 n.d. n.d. n.d. = not determined a) 52 samples, 4 Gammarus pulex pooled in each sample b) Calculated from weight after [5] under the assumption of equal proportions of males and females. -S3 -

4 Toxicokinetic experiment Eight replicate beakers of 500 ml pre-aerated APW and one control beaker contained each 20 Gammarus pulex and five leaf discs as food and shelter. Diazinon ( 14 C-labelled, carrier acetone < 0.03% of test solution) was added to the eight treated beakers (32.3 nmol/l initially) and 1mL of test solutions was sampled immediately after careful stirring (0h) and after 12, 24, 36, 48, 72 hours to quantify diazinon concentrations in the exposure medium. The exposure phase lasted 24 hours. Afterwards organisms were removed from test solutions, rinsed and transferred to new beakers with fresh APW and leaf discs. The subsequent depuration phase lasted until 75 hours after the start of the experiment. The initial exposure concentration of 32.3 nmol/l (corresponds to 38% of the 24h-LC50 of 85 nmol/l) was chosen to ensure that acute toxicity did not strongly affect the organisms, but close enough to the toxic range to be relevant for effect modeling. By choosing a concentration as close to the toxic range as possible, we also maximized the limit of quantification for internal concentrations of diazinon and its biotransformation products. Gammarus pulex were sampled after 4, 7, 13, 23, 28, 32, 39, 48, 73 and 75 hours. Organisms were removed from the water, blotted dry and four Gammarus pulex from different beakers were placed together in pre-weighed glass tubes, weighed and frozen at -20 C until analysis. Four replicate samples, each containing four pooled individual organisms, were taken at each sampling time, except for the last sampling after 75 hours where only two samples could be taken from the remaining organisms. Pulse toxicity experiment Seven replicate beakers per treatment (three treatments A, B, C), three beakers APW control and three beakers solvent controls were used (total 27 beakers). Each contained 500 ml pre-aerated APW and initially 10 Gammarus pulex as well as three leaf discs as food and shelter. Water chemistry parameters were measured throughout the pulse toxicity test and are listed in Table S2. At the start of the experiment all treated beakers were dosed with a mixture of 14 C-labelled and unlabelled diazinon (101 nmol/l initially, <0.06% acetone) and stirred carefully. After 24h, the end of the first pulse, the test organisms were rinsed and transferred to fresh pre-aerated APW and leaf discs. The subsequent -S4 -

5 recovery period lasted 2, 7 and 15 days for treatments A, B and C respectively. APW was changed at intervals (max. 7 days) during recovery periods and leaf discs were added as required to provide food ad libitum. The second pulses were applied exactly like the first pulses, with the same concentration and duration, and were also followed by a recovery period. Aqueous samples (2 ml) were taken immediately after dosing and frequently throughout the experiment, in particular before transfers to fresh APW and at the end of pulses. The number of Gammarus pulex alive was counted every day at approximately the same time. Animals were counted dead if no movement was observed after prodding. The experiment lasted until day 22. Table S2: Water chemistry parameters measured throughout the pulse toxicity test. Beaker Treatment ph Conductivity (µs/cm) O 2 (mg/l) A (dosed) B (dosed) C (dosed) A (dosed) B (dosed) C (dosed) A (clean) B (clean) C (clean) S5 -

6 A (clean) B (clean) C (clean) Control Control Control Chemicals O S P O O * N O O P O O * N HO * N N N N Figure S1: Structure of 14 C-labelled diazinon and its transformation products diazoxon and pyrimidinol. The position of the 14 C label is indicated with an asterisk. -S6 -

7 Acute toxicity test We measured mortality after 24, 48, 72 and 96h in an acute toxicity test with Gammarus pulex and unlabelled diazinon. The acute toxicity test consisted of seven tested concentrations, each with two replicate beakers, one solvent control beaker and one control beaker. Each beaker contained 500 ml of pre-aerated APW and ten randomly assigned Gammarus pulex which were fed ad libitum with three inoculated leaf discs per beaker. Dosing stocks were made from unlabelled material by dilution in acetone. After diazinon was spiked into the APW, beakers were carefully stirred, sealed with parafilm and kept at 13 C under a 12h:12h light/dark regime. Live/dead organisms were counted after 24, 48, 72 and 96h by prodding and observation of movement of appendages. Dead organisms were removed. A sigmoidal dose-response model with variable slope (log-logistic equation) was fitted to the survival date using GraphPad Prism (v. 4.03, GraphPad Software Inc., USA) keeping the parameters bottom and top fixed to 0% and 100% respectively. Table S3: Acute toxicity of diazinon to Gammarus pulex 24h 48h 72h 96h LC50 (nmol/l) a [95% confidence intervals] [79.81 to 90.49] [22.41 to 34.53] [15.90 to 22.08] [12.06 to 15.41] LC50 (μg/l) a [95% confidence intervals] [24.29 to 27.54] [6.82 to 10.51] [4.84 to 6.72] [3.67 to 4.69] Hillslope a) based on nominal concentrations -S7 -

8 Sample processing and analytical methods Aqueous samples were analyzed immediately by adding 10 ml Ecoscint A scintillation cocktail (National Diagnostics, UK) and counting of radioactivity three times for 10 min on a Packard (Tri-Carb 2200CA, Packard, USA) scintillation counter (LSC). Counts were corrected for background activities using control samples. Color quenching and counting efficiency were corrected using the reverse spectrum transform method and the efficiency tracing technique as implemented in the Packard Tri- Carb 2200 CA based on a built-in external standard [6]. Frozen samples of Gammarus pulex were ground with a glass rod after the addition of 1 ml methanol. Another 2.5 ml of methanol were used to rinse the glass rod and added to the sample material. Samples were sonicated in an ultrasonic bath for 3 min and the homogenate filtered (Minisart, 26 mm, pore size: 0.2 μm, hydrophilic, cellulose-, acetate- and surfactant-free membrane). Glass tubes, syringes and filters were rinsed twice with 2 ml methanol which was added to the samples. The sample filtrate was concentrated to about 1 ml at 60 C using a GeneVac (EZ-2 PLUS, Genevac, UK). To achieve sufficient radioactivity two of the four samples from each sampling time were combined, tubes rinsed twice with 1 ml methanol and the combined samples concentrated again to about 1 ml. Hence the final two samples per sampling time comprised a total of eight Gammarus pulex per sample. Recovery and extraction efficiency for pooled samples of more than four organisms was insufficient; therefore the samples were extracted separately and combined during the concentration step. In a final concentration step the combined samples were concentrated under nitrogen flow to 90 μl and 210 μl of distilled water were added to obtain a ratio of 30/70 (v/v) methanol to water. Subsequently samples were split into two aliquots. 100 μl were analysed by LSC after adding 10 ml Ecoscint A scintillation cocktail and another 100 μl were analyzed by HPLC (HP 1100, Agilent) with a radio-detector (500 TR, Packard) to quantify amounts of parent compound and transformation products (HPLC method in table S4). Biotransformation products pyrimidinol and diazoxon as well as the parent -S8 -

9 compound diazinon were identified by spiking unlabelled standard material of these to samples of control organisms during the grinding step and identification of these peaks via UV-detection. Peaks with the same retention time in the chromatogram of the UV-detector and the radio-detector were assumed to originate from identical compounds. Comparison with radioactivity measured by LSC yields the recovery of the HPLC method. The limit of detection (LOD) for concentrations in tissue samples of Gammarus pulex using LSC was calculated as: LOD = mean activity of control samples + 3 standard deviation of control samples and is 2.1 picomol / g wet weight. The minimum detectable amount (MDA) for concentrations in tissue samples of Gammarus pulex using HPLC analysis with radio-detector was calculated according to [6] for each peak and ranged from 23 to 62 picomol / g wet weight for peaks of 0.25 min to 2 min duration respectively. Peaks below MDA were set to zero (see table S6), resulting in lower recovery of the HPLC method. Recoveries of the HPLC method compared to liquid scintillation counting (LSC) ranged from 89% to 100% for samples where peaks of all four compounds where above the minimum detectable amount (MDA) and from 0% to 91% for those samples where peaks were below the MDA (Tables S5 and S6). Table S4: Details of the HPLC method. Column Nucleodur C18 Gravity (125x2x5) Solvent A H 2 0 with 0.1% acetic acid Solvent B Methano l with 0.1% acetic acid Time Gradient Flow Injectio n volume min % Solvent B ml / min μl min Retention time Metabolite_1: ~2.5 Pyrimidinol: ~4.5 Diazoxon: ~12 Diazinon: ~14 -S9 -

10 Table S5: Activity quantified by the HPLC with the radio-detector compared to LSC analyses of the same samples Sample Sampling time Mass of sample (8 Gammarus pulex) Total amount quantified by LSC Total amount a) quantified by HPLC Recovery of HPLC method b) name days mg wet weight nmol / kg wet weight nmol / kg wet weight % T1 / T T2 / T T5 / T T6 / T T9 / T T10 / T T13 / T T14 / T T17 / T T18 / T T21 / T T22 / T T25 / T T26 / T T29 / T T30 / T T33 / T T34 / T T37 / T a) Sum of parent compound and biotransformation products b) The LOD of the LSC is lower than the MDA of the HPLC analysis with radio-detector. Peaks below MDA were set to zero (see table S6), resulting in lower recovery of the HPLC method for those samples (e.g. 0% recovery in T33/T35 and T34/T36). -S10 -

11 Data analysis and modeling Toxicokinetic-toxicodynamic model The model was implemented in OpenModel (v.1.1, downloaded on 9 July 2009, from The model code: // setting the initial values of the differential equations, this part is executed only once, i.e. at // the beginning // Initially the internal concentrations are zero, animals are clean // Those are the compartments used for the TK and biotransformation parameter estimation Cint_diazinon = 0 Cint_diazoxon = 0 Cint_pyrimidinol = 0 Cint_metabolite_1 = 0 // Those compartments are used for the TD parameter estimation and survival modeling Cinternal_diazinon_1 = 0 Cinternal_diazoxon_1 = 0 D1 = 0 H1 = 0 Cinternal_diazinon_2 = 0 Cinternal_diazoxon_2 = 0 D2 = 0 H2 = 0 Cinternal_diazinon_2 = 0 Cinternal_diazoxon_2 = 0 D3 = 0 H3 = 0 Hb = 0 // this part is executed in each step, define the differential equations here // TK AND BIOTRANSFORMATION PARAMETER ESTIMATION // written by Roman Ashauer, Eawag, Switzerland, 2009, roman.ashauer@eawag.ch // This is the model for toxicokinetics of diazinon in Gammarus pulex, including activation and // biotransformation // First order kinetics for all processes // The formation of Pyrimidinol is modelled depending on the sum of Diazinon and Diazoxon // The two pathways of Pyrimidinol formation can not be distinguished based on our data // The elimination rates for Diazinon and Diazoxon also include those molecules that were transformed to // Pyrimidinol // The biotransformation rates to pyrimidinol are not explicitly simulated in the differential equations // for Diazinon and Diazoxon // Nevertheless the time courses of all four entities (Diazinon, Diazoxon, Pyrimidinol, Metabolite_1) // are simulated appropriately // Cwater in nanomol per L or picomol per ml --> Cinternal in picomol per g wet weight Cw = water.cwater(t) // This part is the toxicologically relevant part, where the time-course of Diazoxon (toxic entity) is // simulated Cint_diazinon.rate = kin_diazinon * Cw - Cint_diazinon * k_el_diazinon - k_activation * Cint_diazinon Cint_diazoxon.rate = k_activation * Cint_diazinon - k_el_diazoxon * Cint_diazoxon // Here we just calculate the sum of Diazinon and Diazoxon concentrations SumDiaz_Oxon = Cint_diazinon + Cint_diazoxon // Here we calculate the formation of Pyrimidinol and subsequently Metabolite_1 Cint_pyrimidinol.rate = k_formation_pyrimidinol * SumDiaz_Oxon - kout_pyrimidinol * Cint_pyrimidinol - k_metabolisation_1 * Cint_pyrimidinol Cint_metabolite_1.rate = k_metabolisation_1 * Cint_pyrimidinol - kout_metabolite_1 * Cint_metabolite_1 // TD AND SURVIVAL MODELLING // written by Roman Ashauer, Eawag, Switzerland, 2009, roman.ashauer@eawag.ch // Cwater in input files is in nanomol/l (equal to picomol/ml) --> kk has units of g/(picomol*day) // Divide Cwater by 1000 to make it micromol/l (equal to nanomol/ml) --> kk has units of g/(nanomol*day) // This is better because the absolute values of kk are less prone to numerical problems // for example kk=0.667 g/(nanomol*day) is better than kk= g/(picomol*day) -S11 -

12 Cw1 = water_expa_t1.cw(t)/1000 Cw2 = water_expa_t2.cw(t)/1000 Cw3 = water_expa_t3.cw(t)/1000 // This is the background hazard (mortality in controls) for experiment A Hb.rate = hb_rate Sb = exp(-hb) // This is the Threshold Damage Model (TDM), incl. biotransformation, for treatment 1 Cinternal_diazinon_1.rate = kin_diazinon * Cw1 - Cinternal_diazinon_1 * k_el_diazinon - k_activation * Cinternal_diazinon_1 Cinternal_diazoxon_1.rate = k_activation * Cinternal_diazinon_1 - k_el_diazoxon * Cinternal_diazoxon_1 D1.rate = kk*cinternal_diazoxon_1 - kr*d1 H1.rate = max(d1-threshold,0) S1 = exp(-h1)*sb // This is the Threshold Damage Model (TDM), incl. biotransformation, for treatment 2 Cinternal_diazinon_2.rate = kin_diazinon * Cw2 - Cinternal_diazinon_2 * k_el_diazinon - k_activation * Cinternal_diazinon_2 Cinternal_diazoxon_2.rate = k_activation * Cinternal_diazinon_2 - k_el_diazoxon * Cinternal_diazoxon_2 D2.rate = kk*cinternal_diazoxon_2 - kr*d2 H2.rate = max(d2-threshold,0) S2 = exp(-h2)*sb // This is the Threshold Damage Model (TDM), incl. biotransformation, for treatment 3 Cinternal_diazinon_3.rate = kin_diazinon * Cw3 - Cinternal_diazinon_3 * k_el_diazinon - k_activation * Cinternal_diazinon_3 Cinternal_diazoxon_3.rate = k_activation * Cinternal_diazinon_3 - k_el_diazoxon * Cinternal_diazoxon_3 D3.rate = kk*cinternal_diazoxon_3 - kr*d3 H3.rate = max(d3-threshold,0) S3 = exp(-h3)*sb Parameter estimation Model parameters were estimated by model fitting in four steps (Table S8) using OpenModel (v1.1, University of Nottingham, UK, 2009). The measured diazinon concentrations in the exposure water served as model input for all simulations. In steps one and two the toxicokinetic parameters were estimated from internal concentration data measured in the toxicokinetic experiment, whereas in the third step toxicodynamic parameters were estimated from the survival data measured in the pulse toxicity experiment keeping the TK parameters fixed. No weighing of data was applied in those first three steps. In the first three steps, groups of parameters were estimated by fitting the model to the relevant data only (Table S8). In the fourth step all parameters were fitted to all data at the same time using Markov-Chain Monte- Carlo. There are twelve model parameters in total, four different data sets of internal concentrations, i.e. diazinon, diazoxon, pyrimidinol and metabolite_1, as well as survival data for the three treatments and the controls. As we used data with very different absolute numbers, numbers of data points and units in this fourth step, we scaled each data series according to their contribution to the objective function. Each data series was multiplied with a factor such that the contribution of all data series to the objective function was equal when calculated based on the prior parameterization. -S12 -

13 Settings for Marquardt parameter estimation algorithm: Weighing of different types of data: no weights Merit function uses: squared deviations Convergent steps required: 8 Initial lambda: Convergence Merit Function Change Threshold: 0.1 Fractional Change for Derivatives: 0.01 Parameter Change Brake: 1 Default Minimum Move: Settings for MCMC parameter estimation algorithm: Number of steps: Weighing of different types of data: scaling of data series according to weight in objective function Merit function uses: squared deviations Prior distributions: uniform, factor 0.1 to factor 10 around Marquardt best fit values Walk: 5% Sigma options: estimate sigma Randomize initial values: no Burn in: 50% -S13 -

14 Results and discussion Toxicokinetic experiment Table S6: Concentrations of diazinon, diazoxon, pyrimidinol and metabolite_1 in Gammarus pulex, during the toxicokinetic experiment as quantified by HPLC with radio-detector (see Figure 2). Sample name Sampling time days Diazinon Diazoxon Pyrimidinol Metabolite_1 nmol / kg wet weight nmol / kg wet weight nmol / kg wet weight nmol / kg wet weight T1 / T T2 / T T5 / T T6 / T T9 / T T10 / T T13 / T T14 / T T17 / T T18 / T T21 / T T22 / T T25 / T T26 / T T29 / T T30 / T T33 / T T34 / T T37 / T S14 -

15 Carry-over toxicity Table S7: Statistical tests for significance of carry-over toxicity in the mortality data following the second pulses (A2, B2, C2). Comparison Duration a Proportions dead p-value in binomial test of proportions p-value in Gehan-Wilcoxon test with Peto & Peto modification A2 vs. C1a 16 d 46/55 vs. 32/70 <0.001 < % vs. 46% B2 vs. C1b 14 d 35/46 vs. 30/70 <0.001 < % vs. 43% C2 vs. B1 6 d 19/38 vs. 23/ b b 50% vs. 33% a) Mortalities from second pulses are compared with mortalities following first pulses in another treatment to assure independence of data. Those comparisons with the longest possible duration of the comparison are chosen to maximise the information used in the test. b) The duration of C2 is rather short and the mortality has not yet returned to background levels which may contribute, in addition to recovery of the organisms, to the finding that the difference to B1 has a 8% or 10% probability of being due to chance. -S15 -

16 Table S8: Number of living organisms in each beaker during the pulse toxicity experiment (see Figure 3). Treatment A A A A A A A B B B B B B B C C C C C C C Solvent controls Controls Beaker Da y S16 -

17 Toxicokinetic-toxicodynamic parameters and model fit Table S9: Stepwise fitting of toxicokinetic and toxicodynamic model parameters. Step 1. Toxicokinetics of diazinon and diazoxon 2. Toxicokinetics of pyrimidinol and metabolite_1 3. Toxicodynamics 4. Simultaneous fit of all parameters Fitting method Marquard t Marquard t Marquard t Data used Estimated parameters Units Initials / Priors a Best fit / Posteriors (mean ± SD) C internal diazinon, C internal diazoxon C internal pyrimidinol, C internal metabolite_1 Survival data (incl. controls) k activation k elimination diazinon k elimination diazoxon k in diazinon k formation pyrimidinol k metabolisation_1 k out pyrimidinol k out metabolite_1 h B k k k r threshold MCMC All data k activation k elimination diazinon k elimination diazoxon k in diazinon k formation pyrimidinol k metabolisation_1 k out pyrimidinol k out metabolite_1 h B k k k r threshold ml g -1 w.w g w.w. nmol day - ml g -1 w.w. g w.w. nmol b 3.51 b 288 b to to to to to to to to to to to to ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± S17 -

18 a) The priors for the fourth step (MCMC fit) were uninformative, uniform distributions ranging from factor 0.1 to factor 10 around the best fit estimates from steps one to three (Marquardt fits). b) These initial values were taken from a toxicokinetic study where total radioactivity was measured in the organisms (Ashauer et al. 2010, in press). -S18 -

19 Table S10: Times to steady-state for toxicokinetic rate constants which affect the time to achieve steady-state for internal concentrations of diazoxon. Parameter Mean value from best fit [ ] Time to 95% steady-state (t 95 ) a [days] k activation k elimination diazinon k elimination diazoxon a) Calculated as t 95 = - ln(1-0.95)/ k i for each parameter Table S11: Goodness of fit statistics. Data Mean error Pearson s r 2 Survival treatment A 21.1 % 0.94 Survival treatment B 9.8 % 0.98 Survival treatment C 2.5 % 0.99 Survival treatment Controls 3.3 % 0.97 C internal diazinon 50.3 % 0.95 C internal diazoxon 45.1 % 0.82 C internal pyrimidinol 31.9 % 0.92 C internal metabolite_ % S19 -

20 Concentrations in the water phase used as input for modeling Table S12: Aqueous concentration of diazinon in toxicokinetic experiment. Time (days) Concentration of diazinon in water (nmol / L) Comment measured measured measured transfer to fresh APW measured measured measured extrapolated from previous data point to extent input data after last time point in internal concentrations inserted, all input data files need to have the same duration -S20 -

21 Table S13: Aqueous concentration of diazinon in pulse toxicity experiment treatment A. Time (days) Concentration of diazinon in water (nmol / L) Comment measured measured transfer to fresh APW measured measured measured transfer to fresh APW measured measured inserted, all input data files need to have the same duration Table S14: Aqueous concentration of diazinon in pulse toxicity experiment treatment B. Time (days) Concentration of diazinon in water (nmol / Comment L) measured measured transfer to fresh APW 8 0 measured measured measured transfer to fresh APW 15 0 measured inserted, all input data files need to have the same duration -S21 -

22 Table S15: Aqueous concentration of diazinon in pulse toxicity experiment treatment C. Time (days) Concentration of diazinon in water (nmol / L) Comment measured measured transfer to fresh APW measured measured 16 0 measured measured measured transfer to fresh APW measured References used in the supporting information 1. Maltby, L., The Use of the Physiological Energetics of Gammarus-Pulex to Assess Toxicity - a Study Using Artificial Streams. Environmental Toxicology and Chemistry 1992, 11, (1), Maltby, L.; Clayton, S. A.; Wood, R. M.; McLoughlin, N., Evaluation of the Gammarus pulex in situ feeding assay as a biomonitor of water quality: Robustness, responsiveness, and relevance. Environmental Toxicology and Chemistry 2002, 21, (2), Maltby, L.; Hills, L., Spray drift of pesticides and stream macroinvertebrates: Experimental evidence of impacts and effectiveness of mitigation measures. Environmental Pollution 2008, 156, (3), Naylor, C.; Maltby, L.; Calow, P., Scope for growth in Gammarus-pulex, a fresh-water benthic detritivore. Hydrobiologia 1989, , (1), Sutcliffe, D. W.; Carrick, T. R.; Willoughby, L. G., Effects of diet, body size, age and temperature on growth rates in the amphipod Gammarus pulex. Freshwater Biology 1981, 11, (2), Packard, Operation Manual. Tri-Carb Liquid Scintiallation Analyzers Models 2200 CA and 2250 CA. Packard Instrument Company: Downers Grove, IL, USA, S22 -

23 7. Ashauer, R.; Caravatti, I.; Hintermeister, A.; Escher, B.I., Bioaccumulation kinetics of organic xenobiotic pollutants in the freshwater invertebrate Gammarus pulex modelled with prediction intervals. Environmental Toxicology and Chemistry, 2010, in press. -S23 -