What to do with NOECS/NOELS--prohibition or innovation?

Fish early life stage toxicity prediction from acute daphnid toxicity and quantum chemistry

One step towards reduced animal testing is the use of in silico screening methods to predict toxicity of chemicals, which requires high-quality data to develop models that are reliable and clearly interpretable. We compiled a large data set of fish early life stage no observed effect concentration endpoints (FELS NOEC) based on published data sources and internal studies, containing data for 338 molecules. Furthermore, we developed a new quantitative structure-activity-activity relationship (QSAAR) model to inform estimation of this endpoint using a combination of dimensionality reduction, regularization, and domain knowledge. In particular, we made use of a sparse partial least squares algorithm (sPLS) to select relevant variables from a huge number of molecular descriptors ranging from topological to quantum chemical properties. The final QSAAR model is of low complexity, consisting of 2 latent variables based on 8 molecular descriptors and experimental Daphnia magna acute data (EC50, 48 h). We provide a mechanistic interpretation of each model parameter. The model performs well, with a coefficient of determination r ² of 0.723 on the training set (cross-validated q ² = 0.686) and comparable predictivity on a test data set of chemically related molecules with experimental Daphnia magna data (r ² _test = 0.687, RMSE = 0.793 log units).

Hormesis-induced gap between the guidelines and reality in ecological risk assessment

Guidelines of ecological risk assessment (ERA) used worldwide, based on S-shaped threshold dose-response curve, fail to consider hormesis, a biphasic dose-response model represented as a J-shaped or an inverted U-shaped curve, that occurs in real-life environment. Now that humans are routinely exposed to chemicals below the threshold where hormetic stimulation prevails, it is noteworthy that over-strictness about chemical control also means a waste of limited resources. So hormesis leads to the gap between guidelines with S-shaped model and reality with hormesis model concerning ERA. In this study, hormetic effects of sulfachloropyridazine (SCP) on the bioluminescence of Aliivibrio fischeri (A. f) under 41 conditions to simulate the real environment were investigated and compared with ERA practice by some parameters, such as no observed effect concentration (NOEC), hormetic-stimulatory range (HSR) and goal concentration (GC). Not only is the reproducibility of hormesis in real-life contexts confirmed, binomial distribution (p = 0.644 > 0.05) of the relative position of GC and HSR is also found, revealing a 50% probability for GC to falls in HSR, which proves the over-strictness of ERA both qualitatively and quantitatively. This study provides a novel view for ERA that hormetic principles should dominate, and conditions where S-shaped dose-response model works should be singled out on a specific basis to bridge the hormesis-induced gap.

Safety assessment of gasification biochars using Folsomia candida (Collembola) ecotoxicological bioassays

Biochar is a product of the thermal decomposition of biomass under a limited supply of oxygen and can be deriving from pyrolysis or gasification. As the product is rich in highly recalcitrant carbon, it has been proposed as a soil amendment to improve soil fertility and to stock carbon in soils. However, the contaminant compounds present in biochar could represent potential environmental threats. The gasification biochar is a promising by-product, but its effects on soil microarthropods are still nearly unknown. The aim of this study was to assess, using a prognosis approach, any ecotoxicological consequences of four biochars (conifer, poplar, grape marc, and wheat straw) on the springtail Folsomia candida. This was assessed through a series of tests: an avoidance behavior test, a survival and reproduction test, and a test based on the hatching of eggs. Biochars were tested at different concentrations (pulverized and diluted w/w with an artificial standard soil). The results showed that the springtails did not tend to avoid the biochars' substrates up to the rate of 2-5%, but any higher levels of concentration caused the animals to keep away from it. While mortality was negatively affected only in the grape marc biochar, reproduction was significantly reduced in all biochars considered. The hatching of the eggs was anticipated at even the lowest concentrations of herbaceous biochars, while a severe delay was observed in both concentrations tested of the conifer biochar. The endpoints considered were negatively affected by pH, polycyclic aromatic hydrocarbons, and heavy metals (in order of importance). The findings confirmed the potential adverse effects that gasification biochars could have on soil microarthropods and demonstrated the necessity of introducing these tests into biochar characterization protocols.

Don't be fooled-A no-observed-effect concentration is no substitute for a poor concentration-response experiment

Renowned mathematician and science historian Jacob Bronowski once defined science as "the acceptance of what works and the rejection of what does not" and noted "that needs more courage than we might think." Such would also seem to be the case with no-observed-effect concentrations (NOECs) and no-observed-effect levels in ecotoxicology. Compelling arguments were advanced more than a quarter of a century ago as to why the use of a model to describe the concentration-response relationship was preferable to an isolated metric, with the NOEC singled out as a particularly poor toxicity measure. In the ensuing years numerous articles critical of the NOEC have been written, with some calling for an outright ban on its use. More recently, arguments have been made for the retention of NOECs, with supporters suggesting that this metric is particularly useful in situations where the concentration-response relationship is weak or nonexistent. In addition, it has been claimed that there are situations in ecotoxicology where suitable models are simply not available. These arguments are not correct, and they also have impeded the decades-overdue incorporation of numerous recommendations based on research that NOECs should no longer be used. In the present study the authors counter some of the most recent claims in support of NOECs and provide new insights for 1 class of problem claimed not to be amenable to such modeling. They are confident that similar insights will be developed as further original research in this area is undertaken. Environ Toxicol Chem 2016;35:2141-2148. © 2016 SETAC.

Comment on ET&C perspectives, November 2015-A holistic view

In response to a recent collection of perspectives published in Environmental Toxicology and Chemistry, the authors argue that there is little value in revisiting and rehashing the well-documented issues around toxicity metrics, competing statistical paradigms, legitimacy of theoretical constructs for species sensitivity distributions, and a number of other unresolved (and perhaps unresolvable) attendant statistical issues that have occupied journal space for more than 30 yr. This is not to say that these matters are unimportant-they are; however, the discussion on these topics is mature, with very few new insights being offered. To move forward on some of these seemingly intractable issues, the authors suggest the ecotoxicological community would be better served by the formation of a subdiscipline of "statistical ecotoxicology," where professional statisticians and ecotoxicologists work in unison. As it currently stands, statistical developments in ecotoxicology are not necessarily undertaken or peer-reviewed by professional statisticians, a situation that has no doubt contributed to the lack of real progress on important recommendations such as the phasing out of no-observed-effect concentrations. Environ Toxicol Chem 2016;35:1337-1339. © 2016 SETAC.

Characterization of ecological risks from environmental releases of decamethylcyclopentasiloxane (D5)

Decamethylcyclopentasiloxane (D5) is used in personal care products and industrial applications. The authors summarize the risks to the environment from D5 based on multiple lines of evidence and conclude that it presents negligible risk. Laboratory and field studies show that D5 is not toxic to aquatic organisms or benthic invertebrates up to its solubility limit in water or porewater or its sorptive capacity in sediment. Comparison of lipid-normalized internal concentrations with measured concentrations in benthos indicates that field-collected organisms do not achieve toxic levels of D5 in their tissues, suggesting negligible risk. Exposure to D5 resulted in a slight reduction of root biomass in barley at test concentrations 2 orders of magnitude greater than measured D5 levels in biosolids-amended soils and more than twice as high as the maximum calculated sorptive capacity of the soil. No effects were observed in soil invertebrates exposed to similar concentrations, indicating that D5 poses a de minimis risk to the terrestrial environment. High rates of metabolism and elimination of D5 compared with uptake rates from food results in biodilution in the food web rather than biomagnification, culminating in de minimis risk to higher trophic level organisms via the food chain. A fugacity approach substantiates all conclusions that were made on a concentration basis.

Constructing Time-Resolved Species Sensitivity Distributions Using a Hierarchical Toxico-Dynamic Model

Classical species sensitivity distribution (SSD) is used to assess the threat to ecological communities posed by a contaminant and derive a safe concentration. It suffers from several well-documented weaknesses regarding its ecological realism and statistical soundness. Criticism includes that SSD does not take time-dependence of the data into account, that safe concentrations obtained from SSD might not be entirely protective of the target communities, and that there are issues of statistical representativity and of uncertainty propagation from the experimental data. We present a hierarchical toxico-dynamic (TD) model to simultaneously address these weaknesses: TD models incorporate time-dependence and allow improvement of the ecological relevance of safe concentrations, while the hierarchical approach affords appropriate propagation of uncertainty from the original data. We develop this model on a published data set containing the salinity tolerance over 72 h of 217 macroinvertebrate taxa, obtained through rapid toxicity testing (RTT). The shrinkage properties of the hierarchical model prove particularly adequate for modeling inhomogeneous RTT data. Taking into account the large variability in the species response, the model fits the whole data set well. Moreover, the model predicts a time-independent safe concentration below that obtained with classical SSD at 72 h, demonstrating under-protectiveness of the classical approach.

Evaluation and comparison of the relationship between NOEC and EC10 or EC20 values in chronic Daphnia toxicity testing

Hypothesis-based no-effect-concentration (NOEC) and regression-based x% effect concentration (ECx) values are common statistical approaches used to summarize ecotoxicological effects. Controversy over the NOEC model has prompted a movement toward discontinuation of the NOEC in favor of ECx, but the best x% effect surrogate for NOEC has not yet been determined. Historically, 10% and 20% effect concentrations (EC10 and EC20) have been treated as NOEC analogs. Given these measurements' importance to ecotoxicology, further understanding of the relationships between NOEC and EC10 or EC20 is crucial. In the present study, a metadataset of daphnid chronic toxicity tests was compiled to analyze the strength and significance of NOEC:EC10 and NOEC:EC20 relationships. The impact of endpoint (e.g., mortality, reproduction) and test condition parameters (e.g., pH, temperature) on NOEC:EC10 and NOEC:EC20 was evaluated. Mortality endpoints were most sensitive 51% of the time, with growth and reproductive endpoints constituting the remainder, underscoring the value of using multiple endpoints to evaluate toxic effects rather than relying on reproduction as the a priori most sensitive endpoint. When test condition parameters were less restricted (e.g., pH, hardness), the NOEC:EC20 association was more robust, suggesting that variability introduced by test implementation increased variability in ECx calculation. The analysis revealed that, overall, EC10 was a more suitable analog than EC20 for NOEC. Recommendations include refinement and reporting of the test parameters pH and hardness to minimize variability in ECx calculation.

Does the Choice of NOEC or EC10 Affect the Hazardous Concentration for 5% of the Species?

We evaluated if the choice of no observed effect concentration (NOEC) or a 10% effect concentration (EC10) affects the hazardous concentrations for 5% of the species (HC5s) estimated from species sensitivity distributions (SSDs). By reviewing available literature reporting NOECs and reanalyzing original toxicity data to estimate EC10s, we developed two SSDs for five chemicals (zinc, lead, nonylphenol, 3,4-dichlorobenzenamine, and lindane) based separately on 9-19 EC10s and NOECs. On average, point estimates of HC5s based on EC10s were 1.2 (range of 0.6-1.9) times higher than those based on NOECs. However, both EC10-based and NOEC-based HC5s estimated for five substances were on the same order of magnitude, and their 95% confidence intervals overlapped considerably. Thus, although EC10 was chosen as a representative of ECx in this study, our results suggest that the choice of ECx (e.g., EC5, EC10, or EC20) or NOEC does not largely affect the resulting HC5s. Therefore, use of NOECs would be acceptable particularly in regulatory contexts, although the NOEC has important shortcomings and should be used with caution.

Derivation of a water quality guideline for aluminium in marine waters

Metal risk assessment of industrialized harbors and coastal marine waters requires the application of robust water quality guidelines to determine the likelihood of biological impacts. Currently there is no such guideline available for aluminium in marine waters. A water quality guideline of 24 µg total Al/L has been developed for aluminium in marine waters based on chronic 10% inhibition or effect concentrations (IC10 or EC10) and no-observed-effect concentrations (NOECs) from 11 species (2 literature values and 9 species tested including temperate and tropical species) representing 6 taxonomic groups. The 3 most sensitive species tested were a diatom Ceratoneis closterium (formerly Nitzschia closterium; IC10 = 18 µg Al/L, 72-h growth rate inhibition) < mussel Mytilus edulis plannulatus (EC10 = 250 µg Al/L, 72-h embryo development) < oyster Saccostrea echinata (EC10 = 410 µg Al/L, 48-h embryo development). Toxicity to these species was the result of the dissolved aluminium forms of aluminate (Al(OH4 (-) ) and aluminium hydroxide (Al(OH)3 (0) ) although both dissolved, and particulate aluminium contributed to toxicity in the diatom Minutocellus polymorphus and green alga Dunaliella tertiolecta. In contrast, aluminium toxicity to the green flagellate alga Tetraselmis sp. was the result of particulate aluminium only. Four species, a brown macroalga (Hormosira banksii), sea urchin embryo (Heliocidaris tuberculata), and 2 juvenile fish species (Lates calcarifer and Acanthochromis polyacanthus), were not adversely affected at the highest test concentration used.

Statistical handling of reproduction data for exposure-response modeling

Reproduction data collected through standard bioassays are classically analyzed by regression in order to fit exposure-response curves and estimate ECx values (x% effective concentration). But regression is often misused on such data, ignoring statistical issues related to (i) the special nature of reproduction data (count data), (ii) a potential inter-replicate variability, and (iii) a possible concomitant mortality. This paper offers new insights in dealing with those issues. Concerning mortality, particular attention was paid not to waste any valuable data-by dropping all the replicates with mortality-or to bias ECx values. For that purpose we defined a new covariate summing the observation periods during which each individual contributes to the reproduction process. This covariate was then used to quantify reproduction-for each replicate at each concentration-as a number of offspring per individual-day. We formulated three exposure-response models differing by their stochastic part. Those models were fitted to four data sets and compared using a Bayesian framework. The individual-day unit proved to be a suitable approach to use all the available data and prevent bias in the estimation of ECx values. Furthermore, a nonclassical negative-binomial model was shown to correctly describe the inter-replicate variability observed in the studied data sets.

Pesticide residues and bees--a risk assessment

Bees are essential pollinators of many plants in natural ecosystems and agricultural crops alike. In recent years the decline and disappearance of bee species in the wild and the collapse of honey bee colonies have concerned ecologists and apiculturalists, who search for causes and solutions to this problem. Whilst biological factors such as viral diseases, mite and parasite infections are undoubtedly involved, it is also evident that pesticides applied to agricultural crops have a negative impact on bees. Most risk assessments have focused on direct acute exposure of bees to agrochemicals from spray drift. However, the large number of pesticide residues found in pollen and honey demand a thorough evaluation of all residual compounds so as to identify those of highest risk to bees. Using data from recent residue surveys and toxicity of pesticides to honey and bumble bees, a comprehensive evaluation of risks under current exposure conditions is presented here. Standard risk assessments are complemented with new approaches that take into account time-cumulative effects over time, especially with dietary exposures. Whilst overall risks appear to be low, our analysis indicates that residues of pyrethroid and neonicotinoid insecticides pose the highest risk by contact exposure of bees with contaminated pollen. However, the synergism of ergosterol inhibiting fungicides with those two classes of insecticides results in much higher risks in spite of the low prevalence of their combined residues. Risks by ingestion of contaminated pollen and honey are of some concern for systemic insecticides, particularly imidacloprid and thiamethoxam, chlorpyrifos and the mixtures of cyhalothrin and ergosterol inhibiting fungicides. More attention should be paid to specific residue mixtures that may result in synergistic toxicity to bees.

Germination and root elongation bioassays in six different plant species for testing Ni contamination in soil

In vitro short-term chronic phytotoxicity germination and root elongation test were applied to test the effects of nickel (Ni) in seed germination and root elongation in six plants species: Cucumis sativus (Cucurbitaceae), Lepidium sativum and Brassica nigra (Brassicaceae), Trifolium alexandrinum and Medicago sativa (Fabaceae), Phacelia tanacetifolia (Boraginaceae). A naturally Ni rich soil was used to compare the results obtained. Unlike root elongation, germination was not affected by Ni in any of the six species tested. EC50 values, calculated on the root elongation, showed that Ni toxicity decreases in the following order: P. tanacetifolia > B. nigra > C. sativus > L. sativum > M. sativa > T. alexandrinum. The test conducted using soil elutriate revealed a significantly lower effect in both seed germination and root elongation when compared to the results obtained using untreated soil. Conversely, the test performed on soil confirmed the high sensitivity of C. sativus, P. tanacetifolia and L. sativum to Ni.

NOEC and LOEC as merely concessive expedients: two unambiguous alternatives and some criteria to maximize the efficiency of dose-response experimental designs

NOEC and LOEC (no and lowest observed effect concentrations, respectively) are toxicological concepts derived from analysis of variance (ANOVA), a not very sensitive method that produces ambiguous results and does not provide confidence intervals (CI) of its estimates. For a long time, despite the abundant criticism that such concepts have raised, the field of the ecotoxicology is reticent to abandon them (two possible reasons will be discussed), adducing the difficulty of clear alternatives. However, this work proves that a debugged dose-response (DR) modeling, through explicit algebraic equations, enables two simple options to accurately calculate the CI of substantially lower doses than NOEC. Both ANOVA and DR analyses are affected by the experimental error, response profile, number of observations and experimental design. The study of these effects--analytically complex and experimentally unfeasible--was carried out using systematic simulations with realistic data, including different error levels. Results revealed the weakness of NOEC and LOEC notions, confirmed the feasibility of the proposed alternatives and allowed to discuss the--often violated--conditions that minimize the CI of the parametric estimates from DR assays. In addition, a table was developed providing the experimental design that minimizes the parametric CI for a given set of working conditions. This makes possible to reduce the experimental effort and to avoid the inconclusive results that are frequently obtained from intuitive experimental plans.