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Cationic polymer (CP) ecotoxicity is important to understand and investigate as they are widely used in industrial and consumer applications and have shown toxic effects in some aquatic organisms. CPs are identified as “polymers of concern” and are to be prioritized in upcoming regulatory reviews, (e.g., REACH). Algae have generally been found to be the most sensitive trophic level to CP. This study aimed at elucidating the magnitude of cationic polyquaternium toxicity towards algae and to understand key toxicological drivers. A suite of polyquaterniums with varying charge density (charged nitrogen moieties) and molecular weight were selected. Highly charged polyquaternium-6 and -16 were toxic towards the freshwater green microalgae Raphidocelis subcapitata with ErC50-values ranging between 0.12 and 0.41 mg/L. Lower charge density polyquaternium-10 materials had much lower toxicity with ErC50 > 200 mg/L, suggesting that charge density is an important driver of algal toxicity. These levels of toxicity were in line with historic CP data in literature. Algal agglomeration was observed in all tests but was not linked with impacts on algal growth rate. However, agglomeration can pose challenges in the technical conduct of tests and can impair interpretation of results. The toxicity mitigation potential of humic acid was also explored. The addition of 2–20 mg/L humic acid completely mitigated PQ6 and PQ16 toxicity at concentrations higher than clean water ErC50-values. CP toxicity mitigation has also been observed in fish and invertebrate tests, suggesting that CP mitigation should be accounted for in all trophic levels within an environmental safety framework.

The cladocerans Daphnia magna and Ceriodaphnia dubia have been used for decades to assess the hazards of chemicals and effluents, but toxicity data for these species have traditionally been treated separately. Numerous standard acute and chronic test guidelines have been developed for both species. In the present study, data were compiled and curated for acute survival (48 h) and growth and reproduction tests with D. magna (21 days chronic) and C. dubia (7 days chronic) toxicity assays. Orthogonal regressions were developed to statistically compare the acute and chronic sensitivity of D. magna and C. dubia across a diversity of chemicals and modes of action. Acute orthogonal regressions between D. magna and D. pulex, a widely accepted surrogate species, were used to set a data-driven benchmark for what would constitute a suitable D. magna surrogate. The results indicate that there is insufficient evidence to suggest a difference in acute or chronic sensitivity of D. magna and C. dubia in standard toxicity tests. Further, the variability in the acute D. magna and C. dubia regressions were of the same magnitude as that in D. magna and D. pulex regressions. Slope and y-intercept values were also comparable. The absence of significant differences in toxicity values suggests similar species sensitivity in standard tests across a range of chemical classes and modes of action. Environ Toxicol Chem 2022;41:134-147. © 2021 SETAC.

Flexible, rapid, and predictive approaches that do not require the use of large numbers of vertebrate test animals are needed because the chemical universe remains largely untested for potential hazards. Development of robust new approach methodologies and nontesting approaches requires the use of existing information via curated, integrated data sets. The ecological threshold of toxicological concern (ecoTTC) represents one such new approach methodology that can predict a conservative de minimis toxicity value for chemicals with little or no information available. For the creation of an ecoTTC tool, a large, diverse environmental data set was developed from multiple sources, with harmonization, characterization, and information quality assessment steps to ensure that the information could be effectively organized and mined. The resulting EnviroTox database contains 91 217 aquatic toxicity records representing 1563 species and 4016 unique Chemical Abstracts Service numbers and is a robust, curated database containing high‐quality aquatic toxicity studies that are traceable to the original information source. Chemical‐specific information is also linked to each record and includes physico‐chemical information, chemical descriptors, and mode of action classifications. Toxicity data are associated with the physico‐chemical data, mode of action classifications, and curated taxonomic information for the organisms tested. The EnviroTox platform also includes 3 analysis tools: a predicted‐no‐effect concentration calculator, an ecoTTC distribution tool, and a chemical toxicity distribution tool. Although the EnviroTox database and tools were originally developed to support ecoTTC analysis and development, they have broader applicability to the field of ecological risk assessment. Environ Toxicol Chem 2019;9999:1–12. © 2019 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals, Inc. on behalf of SETAC.

Algal toxicity studies are required by regulatory agencies for a variety of purposes including classification and labeling and environmental risk assessment of chemicals. Algae are also frequently the most sensitive taxonomic group tested. Acute to chronic ratios (ACRs) have been challenging to derive for algal species because of the complexities of the underlying experimental data including: a lack of universally agreed upon algal inhibition endpoints; evolution of experimental designs over time and by different standardization authorities; and differing statistical approaches (e.g., regression versus hypothesis-based effect concentrations). Experimental data for developing globally accepted algal ACRs have been limited because of data availability, and in most regulatory frameworks an ACR of 10 is used regardless of species, chemical type or mode of action. Acute and chronic toxicity (inhibition) data on 17 algal species and 442 chemicals were compiled from the EnviroTox database (https://envirotoxdatabase.org/) and a proprietary database of algal toxicity records. Information was probed for growth rate, yield, and final cell density endpoints focusing primarily on studies of 72 and 96 h duration. Comparisons of acute and chronic data based on either single (e.g., growth rate) and multiple (e.g., growth rate, final cell density) endpoints were used to assess acute and chronic relationships. Linear regressions of various model permutations were used to compute ACRs for multiple combinations of taxa, chemicals, and endpoints, and showed that ACRs for algae were consistently around 4 (ranging from 2.43 to 5.62). An ACR of 4 for algal toxicity is proposed as an alternative to a default value of 10, and recommendations for consideration and additional research and development are provided.

Derivation of Predicted No Effect Concentrations (PNECs) for aquatic systems is the primary deterministic form of hazard extrapolation used in environmental risk assessment. Depending on the data availability, different regulatory jurisdictions apply application factors (AFs) to the most sensitive measured endpoint to derive the PNEC for a chemical. To assess differences in estimated PNEC values, two PNEC determination methodologies were applied to a curated public database using the EnviroTox Platform ( www.EnviroToxdatabase.org ). PNECs were derived for 3647 compounds using derivation procedures based on example US EPA and a modified European Union chemical registration procedure to allow for comparisons. Ranked probability distributions of PNEC values were developed and 5th percentile values were calculated for the entire dataset and scenarios where full acute or full chronic data sets were available. The lowest PNEC values indicated categorization based on chemical attributes and modes of action would lead to improved extrapolations. Full acute or chronic datasets gave measurably higher 5th percentile PNEC values. Algae were under-represented in available ecotoxicity data but drove PNECs disproportionately. Including algal inhibition studies will be important in understanding chemical hazards. The PNEC derivation logic flows are embedded in the EnviroTox Platform providing transparent and consistent PNEC derivations and PNEC distribution calculations.

Web-based Interspecies Correlation Estimation (ICE) is an application developed to predict the acute toxicity of a chemical from 1 species to another taxon. Web-ICE models use the acute toxicity value for a surrogate species to predict effect values for other species, thus potentially filling in data gaps for a variety of environmental assessment purposes. Web-ICE has historically been dominated by aquatic and terrestrial animal prediction models. Web-ICE models for algal species were essentially absent and are addressed in the present study. A compilation of public and private sector-held algal toxicity data were compiled and reviewed for quality based on relevant aspects of individual studies. Interspecies correlations were constructed from the most commonly tested algal genera for a broad spectrum of chemicals. The ICE regressions were developed based on acute 72-h and 96-h endpoint values involving 1647 unique studies on 476 unique chemicals encompassing 40 genera and 70 species of green, blue-green, and diatom algae. Acceptance criteria for algal ICE models were established prior to evaluation of individual models and included a minimum sample size of 3, a statistically significant regression slope, and a slope estimation parameter ≥0.65. A total of 186 ICE models were possible at the genus level, with 21 meeting quality criteria; and 264 ICE models were developed at the species level, with 32 meeting quality criteria. Algal ICE models will have broad utility in screening environmental hazard assessments, data gap filling in certain regulatory scenarios, and as supplemental information to derive species sensitivity distributions. Environ Toxicol Chem 2016;35:2368-2378. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

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.

Amine oxide (AO) is a cationically charged surfactant at environmental pH and has previously been assessed in the OECD (Organization for Economic Cooperation and Development) High Production Volume (HPV) chemicals program. Typical of cationic chemicals, AO is highly aquatically toxic. In this study we vastly improve the knowledge of AO toxicity by developing acute Quantitative Structure Activity Relationships (QSARs) for an alga ( Desmodesmus subspicatus ), an invertebrate ( Daphnia magna ) and a fish ( Danio rerio ) using the appropriate array of OECD Test Guidelines. A chronic toxicity QSAR was also determined for the most sensitive taxon, Desmodesmus . Pure AO spanning the chain lengths of C8 to C16 were tested individually with trace analytical confirmation of exposures in all tests. The QSARs were all of high quality (R 2 0.92–0.98) with slopes ranging from −0.338 to −0.484. QSARs were then used to normalize toxicity outcomes for a larger, previously published data set used in HPV, European REACH (Registration, Evaluation, and Authorization of Chemicals), and peer reviewed publications. Two additional species, Lemna gibba (macrophyte) and Ankistrodesmus falcatus (alga) were studied in exposures to dodecyl (C12) AO to provide sufficient taxonomic diversity to conduct a Species Sensitivity Distribution (SSD) analysis. The SSD 5th percentile hazardous concentration (HC5) to C12 AO was found to be 0.052 mg/L which is similar to an existing AO 28-d, 3-community periphyton community bioassay normalized to C12 AO (No-observed-effect-concentration or NOEC=0.152 mg/L). The statistical properties of the SSD was probed suggesting that new studies of additional taxa would be required that were at least 10-fold more sensitive than the most sensitive taxon to move the HC5 lower by a factor of 3. The overall AO hazard assessment suggests a large margin of safety relative to published environmental exposure data.

Linear Alkylbenzene Sulfonate (LAS) is high tonnage and widely dispersed anionic surfactant used by the consumer products sector. A range of homologous structures are used in laundry applications that differ primarily on the length of the hydrophobic alkyl chain. This research summarizes the development of a set of acute toxicity QSARs (Quantitative Structure Activity Relationships) for fathead minnows (Pimephales promelas) and daphnids (Daphnia magna, Ceriodaphnia dubia) using accepted test guideline approaches. A series of studies on pure chain length LAS from C10 to C14 were used to develop the QSARs and the robustness of the QSARs was tested by evaluation of two technical mixtures of differing compositions. All QSARs were high quality (R(2) were 0.965-0.997, p 0.0001). Toxicity normalization employing QSARs is used to interpret a broader array of tests on LAS chain length materials to a diverse group of test organisms with the objective of developing Species Sensitivity Distributions (SSDs) for various chain lengths of interest. Mixtures include environmental distributions measured from exposure monitoring surveys of wastewater effluents, various commercial mixtures, or specific chain lengths. SSD 5th percentile hazardous concentrations (HC5s) ranged from 0.129 to 0.254 mg/L for wastewater effluents containing an average of 11.26-12 alkyl carbons. The SSDs are considered highly robust given the breadth of species (n = 19), use of most sensitive endpoints from true chronic studies and the quality of the underlying statistical properties of the SSD itself. The data continue to indicate a low hazard to the environment relative to expected environmental concentrations.

Concentration and time-dependent changes in hepatic gene expression were examined in adult, female zebrafish (Danio rerio) exposed to 0, 0.1, 0.7, 4.9 microg/L of a model androgen, 17alpha-methyldihydrotestosterone (MDHT). At 24 and 168 h, fish were sacrificed and liver was extracted for gene expression analysis using custom Affymetrix GeneChip Zebrafish Genome Microarrays. In an effort to link gene expression changes to higher levels of biological organization, blood was collected for measurement of plasma steroid hormones (17beta-estradiol (E2), testosterone (T)) and vitellogenin (VTG) using ELISA. Body and ovary weight were also measured. A significant reduction in E2 occurred at 24h (0.7 and 4.9 microg/L) and 168 h (4.9 microg/L) following MDHT exposure. In contrast, T was significantly increased at 24h (4.9 microg/L) and 168 h (0.1, 0.7, 4.9 microg/L). 171 and 575 genes were significantly affected in a concentration-dependent manner at either 24 or 168 h by MDHT exposure at p

Web-based Interspecies Correlation Estimation (ICE) is an application developed to predict the acute toxicity of a chemical from 1 species to another taxon. Web-ICE models use the acute toxicity value for a surrogate species to predict effect values for other species, thus potentially filling in data gaps for a variety of environmental assessment purposes. Web-ICE has historically been dominated by aquatic and terrestrial animal prediction models. Web-ICE models for algal species were essentially absent and are addressed in the present study. A compilation of public and private sector-held algal toxicity data were compiled and reviewed for quality based on relevant aspects of individual studies. Interspecies correlations were constructed from the most commonly tested algal genera for a broad spectrum of chemicals. The ICE regressions were developed based on acute 72-h and 96-h endpoint values involving 1647 unique studies on 476 unique chemicals encompassing 40 genera and 70 species of green, blue-green, and diatom algae. Acceptance criteria for algal ICE models were established prior to evaluation of individual models and included a minimum sample size of 3, a statistically significant regression slope, and a slope estimation parameter ≥0.65. A total of 186 ICE models were possible at the genus level, with 21 meeting quality criteria; and 264 ICE models were developed at the species level, with 32 meeting quality criteria. Algal ICE models will have broad utility in screening environmental hazard assessments, data gap filling in certain regulatory scenarios, and as supplemental information to derive species sensitivity distributions. Environ Toxicol Chem 2016;35:2368-2378. Published 2016 Wiley Periodicals Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

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.

Genomic, proteomic, and metabolomic technologies continue to receive increasing interest from environmental toxicologists. This interest is due to the great potential of these technologies to identify detailed modes of action and to provide assistance in the evaluation of a contaminant's risk to aquatic organisms. Our experimental model is the zebrafish (Danio rerio) exposed to reference endocrine disrupting compounds in order to investigate compound-induced changes in gene transcript profiles. Adult, female zebrafish were exposed to 0, 15, 40, and 100ng/L of 17alpha-ethynylestradiol (EE2) and concentration and time-dependent changes in hepatic gene expression were examined using Affymetrix GeneChip Zebrafish Genome Microarrays. At 24, 48, and 168h, fish were sacrificed and liver mRNA was extracted for gene expression analysis (24 and 168h only). In an effort to link gene expression changes to effects on higher levels of biological organization, body and ovary weights were measured and blood was collected for measurement of plasma steroid hormones (17beta-estradiol (E2), testosterone (T)) and vitellogenin (VTG) using ELISA. EE2 exposure significantly affected gene expression, GSI, E2, T, and VTG. We observed 1622 genes that were significantly affected (p< or =0.001) in a concentration-dependent manner by EE2 exposure at either 24 or 168h. Gene ontology (GO) analysis revealed that EE2 exposure affected genes involved in hormone metabolism, vitamin A metabolism, steroid binding, sterol metabolism, and cell growth. Plasma VTG was significantly increased at 24, 48, and 168h (p< or =0.05) at 40 and 100ng/L and at 15ng/L at 168h. E2 and T were significantly reduced following EE2 exposure at 48 and 168h. GSI was decreased in a concentration-dependent manner at 168h. In this study, we identified genes involved in a variety of biological processes that have the potential to be used as markers of exposure to estrogenic substances. Future work will evaluate the use of these genes in zebrafish exposed to weak estrogens to determine if these genes are indicative of exposure to estrogens with varying potencies.

An assay quantifying the loss of antibacterial potency of compounds, originally identified via target-based screening, in the presence of increasing albumin concentration was developed and used as a technique to measure potential association of compounds with proteins unrelated to their molecular target. Minimum inhibitory concentrations (MICs) of test compounds were measured against Staphylococcus aureusstrain ATCC 6538 in the presence of 0-12µM bovine serum albumin (BSA). The linear regression coefficient r 2 for the correlation between MIC and BSAconcentration was ≥ 0.9 for 49 and > 0.5 for 62 out of a total of 69 compounds tested. The slope of these correlations varied widely from < 1 to 99, suggesting that the loss of potency due to a given concentration of BSAcould vary from compound to compound due to wide variation in the apparent stoichiometry for protein-ligand association. Follow-up experiments using additional proteins and a fatty acid, oleic acid, showed that this compound:BSAassociation was not protein specific, but was likely driven by hydrophobicity. The method described in this report can be used to optimize compound design and minimize this undesirable effect. (Journal of Biomolecular Screening2003:555-558)