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The long-term impacts of radiocontaminants (and the associated risks) for ecosystems are still subject to vast societal and scientific debate while wildlife is chronically exposed to various sources and levels of either environmental or anthropogenic ionizing radiation from the use of nuclear energy. The present study aimed to assess induced phenotypical responses in both male and female gammarids after short-term continuous γ-irradiation, acting as a typical well-characterized genotoxic stressor that can interact directly with living matter. In particular, we started characterizing the effects using standardized measurements for biological effects on few biological functions for this species, especially feeding inhibition tests, molting, and reproductive ability, which have already been proven for chemical substances and are likely to be disturbed by ionizing radiation. The results show no significant differences in terms of the survival of organisms (males and females), of their short-term food consumption which is linked to the general health status (males and females), and of the molting cycle (females). In contrast, exposure significantly affected fecundity (number of embryos produced) at the highest dose rates for irradiated females (51 mGy h-1) and males (5 and 51 mGy h-1). These results showed that, in gammarids, reproduction, which is a critical endpoint for population dynamics, is the most radiosensitive phenotypic endpoint, with significant effects recorded on male reproductive capacity, which is more sensitive than in females. Environ Toxicol Chem 2024;43:2071-2079. © 2024 SETAC.

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BACKGROUND: Ambient pollen exposure causes nasal, ocular, and pulmonary symptoms in allergic individuals, but the shape of the exposure-response association is not well characterized. We evaluated this association and determined (1) whether symptom severity differs between subpopulations; (2) how the association changes over the course of the pollen season; and (3) which pollen exposure time lags affect symptoms. METHODS: Adult study participants (n = 396) repeatedly scored severity of nasal, ocular, and pulmonary allergic symptoms, resulting in three composite symptom scores. We calculated hourly individually relevant pollen exposure to seven allergenic plants (alder, ash, birch, hazel, grasses, mugwort, and ragweed) considering personal sensitization and exposure time lags of up to 96 h. We fitted generalized additive mixed models, with a random personal intercept, adjusting for weather and air pollution as potential time-varying confounders. RESULTS: We identified a clear nonlinear positive association between pollen exposure and ocular and nasal symptom severity in the pollen allergy group: Symptom severity increased steeply with increasing exposure initially, but attenuated beyond approximately 80 pollen/m3. We found no evidence of an exposure threshold, below which no symptoms occur. While recent pollen exposure in the last approximately 5 h affected symptoms most, associations lingered for up to 60 h. Grass pollen exposure (compared to tree pollen) and younger age (18-30 years, as opposed to 30-65 years) were both associated with higher nasal and ocular symptom severity. CONCLUSIONS: The lack of a threshold and attenuated dose-response curve may have implications for pollen warning systems, which may be revised to include multiday pollen concentrations in the future.

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Absolute (ALW) and relative (RLW) liver weight changes are sensitive endpoints in repeat-dose rodent toxicity studies, and their changes are often used for quantitative assessment of health effects induced by hepatotoxic chemicals using the benchmark dose-response modeling (BMD) approach. To find biologically relevant liver weight changes to chemical exposures, we evaluated all data available for liver weight changes and associated liver histopathologic findings from the Toxicity Reference Database (ToxRefDB). Our analysis of 389 subchronic mouse and rat studies for 273 chemicals found significant differences in treatment-related ALW and RLW changes between dose groups with and without liver histopathologic changes. In addition, we demonstrate that chemical treatment-induced ALW and RLW changes can predict the presence of histopathologic findings and inform the selection of biologically relevant liver weight changes for BMD modeling and derivation of toxicity values.

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Light is the driving force for photosynthesis. Two techniques are commonly employed to help characterize the relationship between the light environment and photosynthesis in plants.Chlorophyll a fluorescence analysis is used to examine both the capacity for and the efficiency of the conversion of absorbed light into energy for photosynthesis. Additionally, gas exchange analysis is used to assess the utilization of that energy for carbon fixation. These techniques are used either in isolation or in combination to acquire light response curves that measure the response of the plant to sequential changes in irradiance. Light response curves can help users understand photosynthetic mechanisms, evaluate how plants respond to light conditions, or assess the extent of physiological plasticity within plants. In this chapter, we provide a generalized method for acquiring light response curves suitable for both chlorophyll a fluorescence and gas exchange techniques using commercially available apparatus. Depending on the equipment available, these methods can be applied individually or combined to acquire data simultaneously. The methods are broadly applicable to most land plants but are ideally suited to help those that are unfamiliar with these techniques.

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Brepocitinib is an oral selective dual TYK2/JAK1 inhibitor and based on its cytokine inhibition profile is expected to provide therapeutic benefit in the treatment of plaque psoriasis. Efficacy data from a completed Phase 2a study in patients with moderate-to-severe plaque psoriasis were utilized to develop a population exposure-response model that can be employed to inform dose selection decisions for further clinical development. A modeling approach that employs the zero-inflated beta distribution was used to account for the bounded nature and distributional characteristics of the Psoriasis Area and Severity Index (PASI) score data. The developed exposure-response model provided an adequate description of the observed PASI scores across all the treatment arms tested and across both the induction and maintenance dosing periods of the study. In addition, the developed model exhibited a good predictive capacity with regard to the derived responder metrics (e.g., 75%/90%/100% improvement in PASI score [PASI75/90/100]). Clinical trial simulations indicated that the induction/maintenance dosing paradigm explored in this study does not offer any advantages from an efficacy perspective and that doses of 10, 30, and 60 mg once-daily may be suitable candidates for clinical evaluation in subsequent Phase 2b studies.

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The prevalence of standardized toxicity testing in ecotoxicology has largely obscured the notion that toxicity is a function of time as well. The necessity of considering time is vividly demonstrated by observations of delayed mortality, that is, deaths continue to occur even when animals are no longer exposed to a toxicant. In this contribution, I explore to what extent toxicokinetic-toxicodynamic (TKTD) models from the framework of the General Unified Threshold model for Survival (GUTS) can capture delayed mortality, and to what extent this phenomenon can be predicted from short-term standard tests. I use a previously published data set for fluoroquinolones in Daphnia magna that shows strongly delayed mortality (using immobilization as a proxy for death). The model analysis shows that the GUTS stochastic death models can capture delayed mortality in the complete data set with a long recovery phase, but that the delayed effects would not have been predicted from a 2-day standard test. The study underlines the limited information content of standard acute test designs. Toxicokinetic-toxicodynamic modeling offers a handle on the time aspects of toxicity but cannot always be relied on to provide accurate extrapolations based on severely limited standard tests. The phenomenon of delayed toxicity requires more structured study to clarify its prevalence and impact; I discuss several avenues for further investigation. Environ Toxicol Chem 2024;43:1030-1035. © 2024 SETAC.

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A range of new statistical approaches is being developed and/or adopted in ecotoxicology that, when combined, can greatly improve the estimation of no-effect toxicity values from concentration-response (CR) experimental data. In particular, we compare the existing no-effect-concentration (NEC) threshold-based toxicity metric with an alternative no-significant-effect-concentration (NSEC) metric suitable for when CR data do not show evidence of a threshold effect. Using a model-averaging approach, these metrics can be combined to yield estimates of N(S)EC and of their uncertainty within a single analysis framework. The outcome is a framework for CR analysis that is robust to uncertainty in the model formulation, and for which resulting estimates can be confidently integrated into risk assessment frameworks, such as the species sensitivity distribution (SSD). Integr Environ Assess Manag 2024;20:279-293. © 2023 Commonwealth of Australia and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

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We focus on Bayesian inference for survival probabilities in a prime-boost vaccination regime in the development of an Ebola vaccine. We are interested in the heterologous prime-boost regimen (unmatched vaccine deliverys using the same antigen) due to its demonstrated durable immunity, well-tolerated safety profile, and suitability as a population vaccination strategy. Our research is motivated by the need to estimate the survival probability given the administered dosage. To do so, we establish two key relationships. Firstly, we model the connection between the designed dose concentration and the induced antibody count using a Bayesian response surface model. Secondly, we model the association between the antibody count and the probability of survival when experimental subjects are exposed to the Ebola virus in a controlled setting using a Bayesian probability of survival model. Finally, we employ a combination of the two models with dose concentration as the predictor of the survival probability for a future vaccinated population. We implement our two-level Bayesian model in Stan, and illustrate its use with simulated and real-world data. Performance of this model is evaluated via simulation. Our work offers a new application of drug synergy models to examine prime-boost vaccine efficacy, and does so using a hierarchical Bayesian framework that allows us to use dose concentration to predict survival probability.

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Polycyclic aromatic compounds (PACs) present in the water column are considered to be one of the primary contaminant groups contributing to the toxicity of a crude oil spill. Because crude oil is a complex mixture composed of thousands of different compounds, oil spill models rely on quantitative structure-activity relationships like the target lipid model to predict the effects of crude oil exposure on aquatic life. These models rely on input provided by single species toxicity studies, which remain insufficient. Although the toxicity of select PACs has been well studied, there is little data available for many, including transformation products such as oxidized hydrocarbons. In addition, the effect of environmental influencing factors such as temperature on PAC toxicity is a wide data gap. In response to these needs, in the present study, Stage I lobster larvae were exposed to six different understudied PACs (naphthalene, fluorenone, methylnaphthalene, phenanthrene, dibenzothiophene, and fluoranthene) at three different relevant temperatures (10, 15, and 20 °C) all within the biological norms for the species during summer when larval releases occur. Lobster larvae were assessed for immobilization as a sublethal effect and mortality following 3, 6, 12, 24, and 48 h of exposure. Higher temperatures increased the rate at which immobilization and mortality were observed for each of the compounds tested and also altered the predicted critical target lipid body burden, incipient median lethal concentration, and elimination rate. Our results demonstrate that temperature has an important influence on PAC toxicity for this species and provides critical data for oil spill modeling. More studies are needed so oil spill models can be appropriately calibrated and to improve their predictive ability. Environ Toxicol Chem 2023;42:2389-2399. © 2023 SETAC.

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PURPOSE: Functional avoidance radiotherapy uses functional imaging to reduce pulmonary toxicity by designing radiotherapy plans that reduce doses to functional regions of the lung. A phase-II, multi-center, prospective study of 4DCT-ventilation functional avoidance was completed. Pre and post-treatment pulmonary function tests (PFTs) were acquired and assessed pulmonary function change. This study aims to evaluate which clinical, dose and dose-function factors predict PFT changes for patients treated with 4DCT-ventilation functional avoidance radiotherapy. MATERIALS AND METHODS: 56 patients with locally advanced lung cancer receiving radiotherapy were accrued. PFTs were obtained at baseline and three months following radiotherapy and included forced expiratory volume in 1-second (FEV1), forced vital capacity (FVC), and FEV1/FVC. The ability of patient, clinical, dose (lung and heart), and dose-function metrics (metrics that combine dose and 4DCT-ventilation-based function) to predict PFT changes were evaluated using univariate and multivariate linear regression. RESULTS: Univariate analysis showed that only dose-function metrics and the presence of chronic obstructive pulmonary disease (COPD) were significant (p<0.05) in predicting FEV1 decline. Multivariate analysis identified a combination of clinical (immunotherapy status, presence of thoracic comorbidities, smoking status, and age), along with lung dose, heart dose, and dose-function metrics in predicting FEV1 and FEV1/FVC changes. CONCLUSION: The current work evaluated factors predicting PFT changes for patients treated in a prospective functional avoidance radiotherapy study. The data revealed that lung dose- function metrics could predict PFT changes, validating the significance of reducing the dose to the functional lung to mitigate the decline in pulmonary function and providing guidance for future clinical trials.

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PURPOSE: Osteoradionecrosis (ORN) of the mandible is a severe complication following radiotherapy of the head and neck, but not all regions of the mandible may be equally at risk. Therefore our goal was to explore a local dose response relationship for subregions of the mandible. MATERIALS AND METHODS: All oropharyngeal cancer patients treated at our hospital between 2009 and 2016 were reviewed. Follow-up was cut-off at 3 years. For patients that developed ORN, the ORN volume was delineated on the planning CT. Each mandible was divided into 16 volumes of interest (VOIs) based on the location of the dental elements and the presence of ORN in each was scored. Generalized estimating equations were used to build a model for the probability of developing ORN in an element VOI. RESULTS: Of the 219 included patients, 22 developed ORN in 89 element VOIs. Mean dose to the element VOI (odds ratio (OR) = 1.05 per Gy, 95% confidence interval (CI): (1.04,1.07)), pre-radiotherapy extractions of an element ipsilateral to element of interest (OR = 2.81, 95% CI: (1.12,7.05)), and smoking at start of radiotherapy (OR = 3.37, 95% CI: (1.29,8.78)) were significantly associated with an increased probability of ORN in the VOI. CONCLUSION: The developed dose-response model indicates that the probability of ORN varies within the mandible and strongly depends on the local dose, the location of extractions, and smoking.

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The no-effect concentration (NEC) is the preferred threshold metric for single-species toxicity tests applied to derive safe concentration thresholds for contaminants in the environment for use in species sensitivity distributions. However, the NEC is only suitable when concentration-response (C-R) data exhibit a threshold response. We describe an alternative toxicity estimate, the no-significant-effect concentration (NSEC), which is better suited to C-R data for which the response is a monotonically decreasing function of concentration and no threshold effects are evident. We use a flexible, three-parameter sigmoidal function to describe the C-R relationship and detail both Bayesian and frequentist approaches to estimation and inference for the NSEC. While the NSEC is conceptually linked to the traditional no-observed-effect concentration (NOEC), it is a substantial improvement over the NOEC because it decouples the estimate from being directly dependent on the placement of treatment concentrations as well as admitting statements of precision of the resulting toxicity estimate. Environ Toxicol Chem 2023;42:2019-2028. © 2023 Commonwealth of Australia and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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Golimumab was recently evaluated in a phase 2a, randomized, double-blind, placebo-controlled, multicenter study (T1GER study) for safety and efficacy in children and young adults with newly diagnosed type 1 diabetes (T1D). Golimumab showed significant treatment effect where endogenous insulin production was preserved and clinical and metabolic parameters were improved. The objective of this report was to evaluate pharmacokinetic (PK) and pharmacodynamic data from the T1GER study by developing a population pharmacokinetic (PopPK) model and performing exposure-response (ER) analyses. The PopPK model was developed using data from the T1D study and 2 other pediatric studies with golimumab in ulcerative colitis and in polyarticular juvenile idiopathic arthritis. A 1-compartment model with first-order absorption and elimination was applied to describe the concentration-time profiles. Typical parameters normalized to the values in subjects with a standard weight of 70 kg were apparent clearance, 0.850 L/day; apparent volume of distribution, 16.0 L; and absorption rate constant, 1.01/day. From the ER analyses, no clear trends were observed for changes in both C-peptide area under the concentration-time curve and hemoglobin A1c levels for the relatively narrow exposure ranges following the body surface area-based dosing regimen used in this study. In conclusion, the developed PopPK model was able to adequately describe the observed PK of golimumab in patients with T1D. Although golimumab showed significant treatment effect, the ER analyses did not show clear trends within the active treatment group, which may indicate that the exposure from this T1D-specific dosing regimen was at the plateau of the ER curve.

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Recent research has revealed various lethal and sublethal effects of the selective serotonin reuptake inhibitor citalopram hydrobromide on the harpacticoid copepod Nitocra spinipes. In the present study, an individual-based model (IBM) grounded in the dynamic energy budget (DEB) theory was developed to extrapolate said effects to the population level. Using a generic DEB-IBM as a template, the model was designed to be as simple as possible, keeping model components that are outside the scope of the core DEB theory to a minimum. To test the model, a 56-day population experiment was performed at 0, 100, and 1000 µg citalopram hydrobromide L-1 . In the experiment, the populations quickly reached a plateau in the control and at 100 µg L-1 , which was correctly reproduced by the model and could be explained by food limitations hindering further population growth. At 1000 µg L-1 , a clear mismatch occurred: Whereas in the experiment the population size increased beyond the supposed (food competition-induced) capacity, the model predicted a suppression of the population size. It is assumed that the IBM still misses important components addressing population density-regulating processes. Particularly crowding effects may have played an important role in the population experiment and should be further investigated to improve the model. Overall, the current DEB IBM for N. spinipes should be seen as a promising starting point for bioenergetics-based copepod population modeling, which-with further improvements-may become a valuable individual-to-population extrapolation tool in the future. Environ Toxicol Chem 2023;42:1094-1108. © 2023 SETAC.

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INTRODUCTION: Lecanemab is a humanized immunoglobulin G1 (IgG1) monoclonal antibody that preferentially targets soluble aggregated Aß species (protofibrils) with activity at amyloid plaques. Amyloid-related imaging abnormalities (ARIA) profiles appear to differ for various anti-amyloid antibodies. Here, we present ARIA data from a large phase 2 lecanemab trial (Study 201) in early Alzheimer's disease. METHODS: Study 201 trial was double-blind, placebo-controlled (core) with an open-label extension (OLE). Observed ARIA events were summarized and modeled via Kaplan-Meier graphs. An exposure response model was developed. RESULTS: In the phase 2 core and OLE, there was a low incidence of ARIA-E (<10%), with <3% symptomatic cases. ARIA-E was generally asymptomatic, mild-to-moderate in severity, and occurred early (<3 months). ARIA-E was correlated with maximum lecanemab serum concentration and incidence was higher in apolipoprotein E4 (ApoE4) homozygous carriers. ARIA-H and ARIA-E occurred with similar frequency in core and OLE. DISCUSSION: Lecanemab can be administered without titration with modest incidence of ARIA.

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Introduction: Epidemiological studies in children suggested that in utero exposure to chlorpyrifos (CPF), an organophosphate insecticide, may cause developmental neurotoxicity (DNT). We applied quantitative in vitro-in vivo extrapolation (QIVIVE) based on in vitro concentration and non-choline esterase-dependent effects data combined with Benchmark dose (BMD) modelling to predict oral maternal CPF exposure during pregnancy leading to fetal brain effect concentration. By comparing the results with data from epidemiological studies, we evaluated the contribution of the in vitro endpoints to the mode of action (MoA) for CPF-induced DNT. Methods: A maternal-fetal PBK model built in PK-Sim® was used to perform QIVIVE predicting CPF concentrations in a pregnant women population at 15 weeks of gestation from cell lysate concentrations obtained in human induced pluripotent stem cell-derived neural stem cells undergoing differentiation towards neurons and glia exposed to CPF for 14 days. The in vitro concentration and effect data were used to perform BMD modelling. Results: The upper BMD was converted into maternal doses which ranged from 3.21 to 271 mg/kg bw/day. Maternal CPF blood levels from epidemiological studies reporting DNT findings in their children were used to estimate oral CPF exposure during pregnancy using the PBK model. It ranged from 0.11 to 140 µg/kg bw/day. Discussion: The effective daily intake doses predicted from the in vitro model were several orders of magnitude higher than exposures estimated from epidemiological studies to induce developmental non-cholinergic neurotoxic responses, which were captured by the analyzed in vitro test battery. These were also higher than the in vivo LOEC for cholinergic effects. Therefore, the quantitative predictive value of the investigated non-choline esterase-dependent effects, although possibly relevant for other chemicals, may not adequately represent potential key events in the MoA for CPF-associated DNT.

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ETHNOPHARMACOLOGICAL RELEVANCE: Traditional Chinese medicine (TCM) has extensive healing effects on inflammatory diseases with few side effects. Reduning injection (RDNI), a TCM prescription composed of Lonicera japonica Thunb., Gardenia jasminoides Ellis. and Artemisia annua L., is wildly used for treating inflammatory diseases. However, the mechanism of action of RDNI, like most TCM prescriptions, is unclear due to the complexity of relationships between components and their curative effects. AIM OF THE STUDY: To develop a universal systems pharmacology protocol for mechanism modeling of TCM and apply it to reveal the real-time anti-inflammatory effect of Reduning Injection. MATERIALS AND METHODS: Combined with database mining and references, a regulatory mechanism network of inflammation was constructed. A quantitative model was established afterwards by integrating pharmacokinetic data and two network parameters, namely Network Efficiency and Network Flux. The time-dependent and dose-response relationship of RDNI on the regulation of inflammation was then quantitatively evaluated. ELISA tests were performed to verify the reliability of the model. RESULTS: Three cytokines, namely IL-1ß, IL-6 and TNF-α were screened out to be markers for evaluation of the anti-inflammatory effect of RDNI. An HPLC method for the simultaneous determination of 10 RDNI compounds in SD rat plasma was established and then applied to pharmacokinetic studies. Based on compound activity and pharmacokinetic data, the time-dependent effect of RDNI were quantitatively predicted by the pathway network-based modeling procedure. CONCLUSIONS: The quantitative model established in this work was successfully applied to predict a TCM prescription's real-time dynamic healing effect after administration. It is qualified to provide novel insights into the time-dependent and dose-effect relationship of drugs in an intricate biological system and new strategies for investigating the detailed molecular mechanisms of TCM.

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How can and should epidemiologists and risk assessors assemble and present evidence for causation of mortality or morbidities by identified agents such as fine particulate matter or other air pollutants? As a motivating example, some scientists have warned recently that ammonia from the production of meat significantly increases human mortality rates in exposed populations by increasing the ambient concentration of fine particulate matter (PM2.5) in air. We reexamine the support for such conclusions, including quantitative calculations that attribute deaths to PM2.5 air pollution by applying associational results such as relative risks, odds ratios, or slope coefficients from regression models to predict the effects on mortality or morbidity of reducing PM2.5 exposures. Taking an outside perspective from the field of causal artificial intelligence (CAI), we conclude that these attribution calculations are methodologically unsound. They produce unreliable conclusions because they ignore an essential distinction between differences in outcomes observed at different levels of exposure and changes in outcomes caused by changing exposure. We find that multiple studies that have examined associations between changes over time in particulate exposure and mortality risk instead of differences in exposures and corresponding mortality risks have found no clear evidence that observed changes in exposure help to predict or explain subsequent changes in mortality risks. We conclude that there is no sound theoretical or empirical reason to believe that reducing ammonia emissions from farms has reduced or would reduce human mortality risks. More generally, applying CAI principles and methods can potentially improve current widespread practices of unsound causal inferences and policy-relevant causal claims that are made without the benefit of formal causal analysis in air pollution health effects research and in other areas of applied epidemiology and public health risk assessment.

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Oil spill risk and impact assessments rely on time-dependent toxicity models to predict the hazard of the constituents that comprise crude oils and petroleum substances. Dissolved aromatic compounds (ACs) are recognized as a primary driver of aquatic toxicity in surface spill exposure scenarios. However, limited time-dependent toxicity data are available for different classes of ACs to calibrate such models. This study examined the acute toxicity of 14 ACs and 3 binary AC mixtures on Artemia franciscana nauplii at 25 °C. Toxicity tests for 3 ACs were also conducted at 15 °C to evaluate the role of temperature on toxicity. The ACs investigated represented parent and alkylated homocyclic and nitrogen-, sulfur- and oxygen-containing heterocyclic structures with octanol-water partition coefficients (log Kow) ranging from 3.2 to 6.6. Passive dosing was used to expose and maintain concentrations in toxicity tests which were confirmed using fluorometry, and independently validated for 6 ACs using GC-MS analysis. Mortality was assessed at 6, 24, and 48 h to characterize the time course of toxicity. No mortality was observed for the most hydrophobic AC tested, 7,12-dimethylbenz[a]anthracene, due to apparent water solubility constraints. Empirical log LC50 s for the remaining ACs were fit to a linear regression with log Kow to derive a critical target lipid body burden (CTLBB) based on the target lipid model. The calculated 48 h CTLBB of 47.1 ± 8.1 µmol/g octanol indicates that Artemia nauplii exhibited comparable sensitivity to other crustaceans. A steep concentration-response was found across all compounds as evidenced by a narrow range (1.0-3.1) in the observed LC50 /LC10 ratio. Differences in toxicokinetics were noted, and no impacts of temperature-dependence of AC toxicity were found. Toxicity data obtained for individual ACs yielded acceptable predictions of observed binary AC mixture toxicity. Results from this study advance toxicity models used in oil spill assessments.

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