The overall group, name and proposed Modes of Action (MoA) of the antifouling compounds.

a<p>Altenburger, 2011 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096580#pone.0096580-Altenburger3" target="_blank">[88]</a>.</p>b<p>Walker, 2009 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096580#pone.0096580-Walker1" target="_blank">[49]</a>.</p>c<p>Fernandez-Alba et al, 2002 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096580#pone.0096580-FernandezAlba1" target="_blank">[89]</a>.</p>d<p>Zhou et al, 2006 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096580#pone.0096580-Zhou1" target="_blank">[40]</a>.</p><p>Particularly for the fungicides, which have multiple and often undefined modes of action, different target sites are given in different references. For herbicides and fungicides used as pesticides we use the definition of Tomlin 2002 <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096580#pone.0096580-Tomlin1" target="_blank">[29]</a>. For the remaining compounds, the source of the MoA are given as footnotes.</p

Frequency of pesticide antagony, additivity and synergy.

<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096580#pone-0096580-g002" target="_blank">Figure 2A</a> shows the number of times a pesticide belonging to the group of organophosphates, carbamates, azoles, triazines, pyrethroids or some other Mode of Action (other MoA) occur in a binary mixture resulting in antagony (blue bars), concentration additivity (CA) (red bars) or synergy (green bars). In figure B and C, the number of binary combinations of cholinesterase inhibitors (ChE) (The organophosphates and carbamates), azoles (AZ), triazines (TZ) and other Modes of Action (Other) resulting in either antagony, concentration additivity or synergy are shown for mixtures tested on B) auto-tropic organisms (plants and algae, <i>n</i> = 120) or C) heterotrophic organisms (microorganisms and animals, <i>n</i> = 128).</p

Frequency of antifoulant antagony, additivity and synergy.

<p><a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0096580#pone-0096580-g003" target="_blank">Figure 3A</a> shows the number of times each of the antifoulants occur in a binary mixture resulting in antagony (blue bars), concentration additivity (CA) (red bars) or synergy (green bars). Antifoulants occurring in less than 1% of the mixtures were excluded. In figure B and C, the number of binary combinations of photosystem II herbicides (PSII) metal ions or metal containing compounds (Metal) and other organic compounds (Other) resulting in either antagony, concentration additivity or synergy are shown for mixtures tested on B) auto-tropic organisms (plants and algae, <i>n</i> = 23) or C) heterotrophic organisms (microorganisms and animals, <i>n</i> = 80).</p

Cummulated frequency of Model Deviation Ratios.

<p>Cummulated frequency of Model Deviation Ratios. (MDR) of binary mixtures of pesticides (<i>n</i> = 195), metals (<i>n</i> = 20), and antifoulants (<i>n</i> = 103). The hatched interval where 0.5≤MDR≤2 defines the mixtures that deviates less than two-fold from a Concentration Addition predictions. Mixtures having MDR values<0.5 are termed antagonistic, while mixtures with MDR values>2 are synergistic.</p

Dynamic Modeling of Sublethal Mixture Toxicity in the Nematode Caenorhabditis elegans

Dynamic models for toxic effects [toxicokinetic–toxicodynamic (TKTD) models] are increasingly used in the analysis of toxicity data for single-chemical exposure. However, these models also offer a natural extension to the effects of chemical mixtures. Here, we demonstrate how a simple model for the energy budget (DEBkiss) can be used to interpret the effects of cadmium and fluoranthene, in both single and mixed exposure, on the nematode Caenorhabditis elegans. The data for all time points and all end points (growth and reproduction) are combined into a single coherent framework. These modeling results are compared to a more traditional independent-action approach based on the dose–response curves for a single end point at a single time point. The analysis with DEBkiss does not lead to a radically different interpretation of the mixture effects, both indicating an antagonistic interaction in the mixture. The DEBkiss analysis does, however, provide much more insight into the relevant dynamic processes underlying the toxic effect on the organism and allows for the generation of mechanistic hypotheses that can be used to guide further research

Temperature effect on five different endpoints: final brood size (A), Final body length (B), time to first egg (C), lifespan (D) and Population Growth Rate (PGR) (E).

<p>All data are given as a function of the mean temperature of the treatment. Data are given as mean ± s.e.m., apart from PGR which is given with 95% Confidence Intervals (CI) obtained by bootstrapping. Significantly different treatments (ANOVA followed by a Tukey <i>post hoc</i> test) are denoted by different letters. Constant temperature treatments are given in black symbols, treatments varying ± 4°C are given in grey symbols and treatments varying ± 8°C are given in open symbols.</p

Copper exposure effects on traits fitted using the DEBkiss model.

<p>The development of body length (A) and offspring production (B) as a function of time for the 16°C constant treatment combined with 0, 8, 20 and 40 mg Cu L^-1 described by the DEBkiss model. Fits include a Cu-related stress factor (<i>s</i>_<i>Cu</i>, <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140277#pone.0140277.t001" target="_blank">Table 1</a>) on maximum assimilation rate (<i>J</i>^<i>a</i>_<i>Am</i>) and length at puberty (<i>L</i>_<i>p</i>) (R² = 0.97). A mixed stressor prediction including the 8% increase in somatic maintainance obtained when fitting the constant and variable control treatments together, and the Cu-related stress factor ontained from the constant temperature treatment (A, B) is shown together with the body length (C) and offspring production (D) data from the 16 ± 8°C treatment combined with 0, 8, 20 and 40 mg Cu L^-1. Jointly the mixed stressor prediction describes 75% of the variation in the data. The 1 and 3 mg Cu L^-1 data are omitted from the fit, as they increased offspring production, which the DEBkiss model is not parameterised to deal with. Data are presented as mean ± s.e.m.</p

The effects of Cu exposure on traits responses in <i>C</i>. <i>elegans</i> in treatments with an average temperature of 16°C.

<p>The five different endpoints: Final brood size (A), final body length (A), time to first egg (B), lifespan (D) and Population Growth Rate (PGR) (E) for the constant 16°C treatment (filled symbols), the 16 ± 4°C (grey symbols) and the 16 ± 8°C (open symbols) as a function of Cu concentrations in the agar. Data are given as mean ± s.e.m. and are described with a three parameter log-logistic concentration response model, except for TFE. The parameters are given in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140277#pone.0140277.t003" target="_blank">Table 3</a>, together with the concentration-response parameters of the other temperature treatments.</p

Temperature effects on traits fitted using the DEBkiss model.

<p>The development of body length (A) and offspring production (B) as a function of time for the five constant temperature treatments are described by the DEBkiss model including a temperature function (R² = 0.87). Fig C and D shows bodylength and offspring production as a function of time for the constant 16°C treatment and the variable 16 ± 8°C treatment described by the DEBkiss model including an 8% increase in mainainance cost for the variable treatment (R² = 0.87). Data are given as mean ± s.e.m. Model parameters are shown in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0140277#pone.0140277.t002" target="_blank">Table 2</a>.</p

Mechanistic Understanding of the Synergistic Potential of Azole Fungicides in the Aquatic Invertebrate <i>Gammarus pulex</i>

Azole fungicides are known inhibitors of the important enzyme class cytochrome P450 monooxygenases (CYPs), thereby influencing the detoxification of co-occurring substances via biotransformation. This synergism in mixtures containing an azole has mostly been studied by effect measurements, while the underlying mechanism has been less well investigated. In this study, six azole fungicides (cyproconazole, epoxiconazole, ketoconazole, prochloraz, propiconazole, and tebuconazole) were selected to investigate their synergistic potential and their CYP inhibition strength in the aquatic invertebrate <i>Gammarus pulex</i>. The strobilurin fungicide azoxystrobin was chosen as co-occurring substrate, and the synergistic potential was measured in terms of internal concentrations of azoxystrobin and associated biotransformation products (BTPs). Azoxystrobin is biotransformed by various reactions, and 18 BTPs were identified. By measuring internal concentrations of azoxystrobin and its BTPs with high-resolution tandem mass spectrometry in the presence and absence of azole fungicides followed by toxicokinetic modeling, we showed that the inhibition of CYP-catalyzed biotransformation reactions indeed played a role for the observed synergism. However, synergism was only observed for prochloraz at environmentally realistic concentrations. Increased uptake rate constants, an increase in the total internal concentration of azoxystrobin and its BTPs, in vivo assays for measuring CYP activities, and <i>G. pulex</i> video-tracking suggested that the 2-fold increase in bioaccumulation, and, thereby, the raised toxicity of azoxystrobin in the presence of prochloraz is not only caused by inhibited biotransformation but even more by increased azoxystrobin uptake induced by hyperactivity