Unexpected recovery and non-effects predicted with a mixture toxicity implementation in a population model

Current regulations in risk assessment are very substance-based and only regard effects observed in lab-standardized tests on individual organisms. However, in the environment organisms are exposed to mixtures of chemicals that vary in concentration and composition. In addition, effects on individuals will have an effect on populations and higher levels of organisation in the ecosystem. Mechanistic, individual-based models have been proposed to tackle this issue as they can integrate effects observed at the individual level to make an extrapolation of effects at the population level. In addition, mechanistic models can be used to describe the effects of mixtures. Mixture toxicity implementations of the GUTS and DEBtox theory are applied here: damage addition and independent action. Integrating these models in an individual-based implementation, a model is obtained that describes effects of mixtures on Daphnia magna populations. Two population experiment were conducted exposing Daphnia magna mixtures of different compounds (Cu, Zn, alfa-HCH, dicofol and pyrene). These compounds have been selected for their suspected toxicological mode of action. The populations were exposed for 2 months to these compounds, their binary mixtures, and a ternary mixture. The population density over time was recorded bi-weekly in all of the treatments. We calibrated an individual-based model for D. magna based on the individual-level effects of the different substances. We validated the implementation at the population level with the data from the population experiment. We evaluated the different mixture toxicity implementations (i.e. damage addition vs independent action). For Cu, the model was able to predict (unexpectedly) recovery of effects over time. The independent action approach was able to predict the effects for the Cu and Zn mixtures. Overall, we highlight the applicability of mechanistic population models for predicting mixture toxicity effects at the population, based on effects observed on the individual level with individual substances

Evaluating the Theoretical Background of STOFFENMANAGER® and the Advanced REACH Tool

STOFFENMANAGER® and the Advanced REACH Tool (ART) are recommended tools by the European Chemical Agency for regulatory chemical safety assessment. The models are widely used and accepted within the scientific community. STOFFENMANAGER® alone has more than 37 000 users globally and more than 310 000 risk assessment have been carried out by 2020. Regardless of their widespread use, this is the first study evaluating the theoretical backgrounds of each model. STOFFENMANAGER® and ART are based on a modified multiplicative model where an exposure base level (mg m−3) is replaced with a dimensionless intrinsic emission score and the exposure modifying factors are replaced with multipliers that are mainly based on subjective categories that are selected by using exposure taxonomy. The intrinsic emission is a unit of concentration to the substance emission potential that represents the concentration generated in a standardized task without local ventilation. Further information or scientific justification for this selection is not provided. The multipliers have mainly discrete values given in natural logarithm steps (…, 0.3, 1, 3, …) that are allocated by expert judgements. The multipliers scientific reasoning or link to physical quantities is not reported. The models calculate a subjective exposure score, which is then translated to an exposure level (mg m−3) by using a calibration factor. The calibration factor is assigned by comparing the measured personal exposure levels with the exposure score that is calculated for the respective exposure scenarios. A mixed effect regression model was used to calculate correlation factors for four exposure group [e.g. dusts, vapors, mists (low-volatiles), and solid object/abrasion] by using ~1000 measurements for STOFFENMANAGER® and 3000 measurements for ART. The measurement data for calibration are collected from different exposure groups. For example, for dusts the calibration data were pooled from exposure measurements sampled from pharmacies, bakeries, construction industry, and so on, which violates the empirical model basic principles. The calibration databases are not publicly available and thus their quality or subjective selections cannot be evaluated. STOFFENMANAGER® and ART can be classified as subjective categorization tools providing qualitative values as their outputs. By definition, STOFFENMANAGER® and ART cannot be classified as mechanistic models or empirical models. This modeling algorithm does not reflect the physical concept originally presented for the STOFFENMANAGER® and ART. A literature review showed that the models have been validated only at the ‘operational analysis’ level that describes the model usability. This review revealed that the accuracy of STOFFENMANAGER® is in the range of 100 000 and for ART 100. Calibration and validation studies have shown that typical log-transformed predicted exposure concentration and measured exposure levels often exhibit weak Pearson’s correlations (r is <0.6) for both STOFFENMANAGER® and ART. Based on these limitations and performance departure from regulatory criteria for risk assessment models, it is recommended that STOFFENMANAGER® and ART regulatory acceptance for chemical safety decision making should be explicitly qualified as to their current deficiencies.Peer reviewe

Small molecules to regulate the GH/IGF1 axis by inhibiting the growth hormone receptor synthesis

Growth hormone (GH) and insulin-like growth factor-1 (IGF1) play an important role in mammalian development, cell proliferation and lifespan. Especially in cases of tumor growth there is an urgent need to control the GH/IGF1 axis. In this study we screened a 38,480-compound library, and in two consecutive rounds of analogues selection, we identified active lead compounds based on the following criteria: inhibition the GH receptor (GHR) activity and its downstream effectors Jak2 and STAT5, and inhibition of growth of breast and colon cancer cells. The most active small molecule (BM001) inhibited both the GH/IGF1 axis and cell proliferation with an IC50 of 10-30 nM of human cancer cells. BM001 depleted GHR in human lymphoblasts. In preclinical xenografted experiments, BM001 showed a strong decrease in tumor volume in mice transplanted with MDA-MB-231 breast cancer cells. Mechanistically, the drug acts on the synthesis of the GHR. Our findings open the possibility to inhibit the GH/IGF1 axis with a small molecule

Consideration of the bioavailability of metal/metalloid species in freshwaters: experiences regarding the implementation of biotic ligand model-based approaches in risk assessment frameworks

After the scientific development of Biotic Ligand Models (BLMs) in recent decades these models are now considered suitable for implementation in regulatory risk assessment of metals in freshwater bodies. The approach has been developed over several years and has been described in many peer-reviewed publications. The original complex BLMs have been applied in prospective risk assessment reports for metals and metal compounds and are also recommended as suitable concepts for the evaluation of monitoring data in the context of the European Water Framework Directive. Currently, several user-friendly BLM-based bioavailability software tools are available for assessing the aquatic toxicity of a limited number of metals (mainly copper, nickel, and zinc). These tools need only a basic set of water parameters as input (e.g., pH, hardness, dissolved organic matter and dissolved metal concentration). Such tools seem appropriate to foster the implementation in routine water quality assessments. This work aims to review the existing bioavailability-based regulatory approaches and the application of available BLM-based bioavailability tools for this purpose. Advantages and possible drawbacks of these tools (e.g., feasibility, boundaries of validity) are discussed, and recommendations for further implementation are given

Identification and confirmation of ammonia toxicity in contaminated sediments using a modified toxicity identification evaluation approach

Toxicity identification of sediment pore waters from four sites in the Upper Scheldt (Belgium) was assessed using a simplified and discriminative toxicity identification evaluation procedure. The samples from all locations exhibited acute toxicity toward the freshwater crustacean Thamnocephalus platyurus. Toxicity was removed or considerably reduced by the cation exchange resins and air stripping at pH 11. In addition, the toxicity of the pore waters was found to be highly pH dependent. Increased toxicity was observed at higher pH levels, whereas reduced toxicity was found at lower pH levels. Based on these results, ammonia was suggested as the main toxic agent. The presence of ammonia concentrations exceeding the 24-h median lethal concentration and comparison of the toxicity characterization profiles of the pore waters with those of the suspected toxicant supported this hypothesis. Furthermore, a significant positive correlation between the observed toxicity of the pore waters and the expected toxicity (due to the presence of the suspected toxicant) confirmed ammonia as the true toxic agent. Finally, the ratio between the expected ammonia toxicity and the observed toxicity from the characterization tests was approx. 1, meaning that all or most of the observed toxicity was caused by the presence of one toxicant (i.e., ammonia). The developed toxicity identification evaluation procedure is suggested as a usefull tool for the identification and confirmation of toxicants in contaminated sediments