Prevalence of elevated lipoprotein(a) in cardiac rehabilitation patients - results from a large-scale multicentre registry in Germany.

BACKGROUND: Lipoprotein(a) (Lp(a)) is an independent risk factor for myocardial infarction and aortic valve stenosis. European guidelines recommend assessing it at least once in a lifetime, particularly in premature atherosclerotic heart disease. METHODS: A non-interventional registry was conducted at MEDIAN rehabilitation facilities in Germany to assess the frequency of Lp(a) testing in referring acute care hospitals and the prevalence of elevated Lp(a) levels in aortic valve stenosis or premature myocardial infarction. All consecutive patients referred after coronary intervention or aortic valve surgery were included in four cohorts: aortic valve intervention (cohort 1), current/previous myocardial infarction at < 60 years of age (cohorts 2a/2b), and myocardial infarction at ≥ 60 years of age (control). RESULTS: The analysis included 3393 patient records (cohort 1, n = 1063; cohort 2a, n = 1351; cohort 2b, n = 381; control, n = 598). Lp(a) had been determined at the referring hospital in 0.19% (cohort 1), 4.96% (cohort 2a), 2.36% (cohort 2b), and 2.01% (control) of patients. Lp(a) levels were > 50 mg/dL or > 125 nmol/L in 28.79% (cohort 1), 29.90% (cohort 2a), and 36.48% (cohort 2b; p < 0.001) compared to 24.25% (control). Family history of premature cardiovascular disease was reported in 13.45% (cohort 1), 38.56% (cohort 2a), and 32.81% (cohort 2b) compared to 17.89% (control; p < 0.05 for each comparison). CONCLUSIONS: Lp(a) had been rarely assessed in acute management of aortic valve stenosis or premature myocardial infarction despite expanding scientific evidence and guideline recommendation. Given the above-average incidence of elevated Lp(a) levels, awareness for Lp(a) has to increase substantially to better identify and manage high-risk patients.

Comparing Sensitivity of Different Bee Species to Pesticides: A TKTD modeling approach.

Risk assessment for bees is mainly based on data for honey bees; however, risk assessment is intended to protect all bee species. This raises the question of whether data for honey bees are a good proxy for other bee species. This issue is not new and has resulted in several publications in which the sensitivity of bee species is compared based on the values of the 48-h median lethal dose (LD50) from acute test results. When this approach is used, observed differences in sensitivity may result both from differences in kinetics and from inherent differences in species sensitivity. In addition, the physiology of the bee, like its overall size, the size of the honey stomach (for acute oral tests), and the physical appearance (for acute contact tests) also influences the sensitivity of the bee. The recently introduced Toxicokinetic-Toxicodynamic (TKTD) model that was developed for the interpretation of honey bee tests (Bee General Uniform Threshold Model for Survival [BeeGUTS]) could integrate the results of acute oral tests, acute contact tests, and chronic tests within one consistent framework. We show that the BeeGUTS model can be calibrated and validated for other bee species and also that the honey bee is among the more sensitive bee species. In addition, we found that differences in sensitivity between species are smaller than previously published comparisons based on 48-h LD50 values. The time-dependency of the LD50 and the specifics of the bee physiology are the main causes of the wider variation found in the published literature. Environ Toxicol Chem 2024;43:1431-1441. © 2024 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

A spatiotemporally explicit modeling approach for more realistic exposure and risk assessment of off-field soil organisms.

Natural and seminatural habitats of soil living organisms in cultivated landscapes can be subject to unintended exposure by active substances of plant protection products (PPPs) used in adjacent fields. Spray-drift deposition and runoff are considered major exposure routes into such off-field areas. In this work, we develop a model (xOffFieldSoil) and associated scenarios to estimate exposure of off-field soil habitats. The modular model approach consists of components, each addressing a specific aspect of exposure processes, for example, PPP use, drift deposition, runoff generation and filtering, estimation of soil concentrations. The approach is spatiotemporally explicit and operates at scales ranging from local edge-of-field to large landscapes. The outcome can be aggregated and presented to the risk assessor in a way that addresses the dimensions and scales defined in specific protection goals (SPGs). The approach can be used to assess the effect of mitigation options, for example, field margins, in-field buffers, or drift-reducing technology. The presented provisional scenarios start with a schematic edge-of-field situation and extend to real-world landscapes of up to 5 km × 5 km. A case study was conducted for two active substances of different environmental fate characteristics. Results are presented as a collection of percentiles over time and space, as contour plots, and as maps. The results show that exposure patterns of off-field soil organisms are of a complex nature due to spatial and temporal variabilities combined with landscape structure and event-based processes. Our concepts and analysis demonstrate that more realistic exposure data can be meaningfully consolidated to serve in standard-tier risk assessments. The real-world landscape-scale scenarios indicate risk hot-spots that support the identification of efficient risk mitigation. As a next step, the spatiotemporally explicit exposure data can be directly coupled to ecological effect models (e.g., for earthworms or collembola) to conduct risk assessments at biological entity levels as required by SPGs. Integr Environ Assess Manag 2024;20:263-278. © 2023 Applied Analysis Solutions LLC and WSC Scientific GmbH and Bayer AG and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

A Toxicokinetic-Toxicodynamic Modeling Workflow Assessing the Quality of Input Mortality Data.

Toxicokinetic-toxicodynamic (TKTD) models simulate organismal uptake and elimination of a substance (TK) and its effects on the organism (TD). The Reduced General Unified Threshold model of Survival (GUTS-RED) is a TKTD modeling framework that is well established for aquatic risk assessment to simulate effects on survival. The TKTD models are applied in three steps: parameterization based on experimental data (calibration), comparing predictions with independent data (validation), and prediction of endpoints under environmental scenarios. Despite a clear understanding of the sensitivity of GUTS-RED predictions to the model parameters, the influence of the input data on the quality of GUTS-RED calibration and validation has not been systematically explored. We analyzed the performance of GUTS-RED calibration and validation based on a unique, comprehensive data set, covering different types of substances, exposure patterns, and aquatic animal species taxa that are regularly used for risk assessment of plant protection products. We developed a software code to automatically calibrate and validate GUTS-RED against survival measurements from 59 toxicity tests and to calculate selected model evaluation metrics. To assess whether specific survival data sets were better suited for calibration or validation, we applied a design in which all possible combinations of studies for the same species-substance combination are used for calibration and validation. We found that uncertainty of calibrated parameters was lower when the full range of effects (i.e., from high survival to high mortality) was covered by input data. Increasing the number of toxicity studies used for calibration further decreased parameter uncertainty. Including data from both acute and chronic studies as well as studies under pulsed and constant exposure in model calibrations improved model predictions on different types of validation data. Using our results, we derived a workflow, including recommendations for the sequence of modeling steps from the selection of input data to a final judgment on the suitability of GUTS-RED for the data set. Environ Toxicol Chem 2024;43:197-210. © 2023 Bayer AG and The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Aquatic macrophyte growth season in Central and Northern European Union and the implications for aquatic macrophyte risk assessments for herbicides.

Under current European Union regulation, the risks to aquatic organisms must be assessed for uses of plant protection products (PPPs) that may result in exposure to the environment. For herbicidal PPPs, aquatic macrophytes are often the most sensitive taxa. For some herbicidal modes of action, macrophytes may be affected only while they are actively growing. For the risk assessment, it is therefore useful to know whether application timings would result in surface water exposure during periods when aquatic macrophytes are actively growing (therefore potentially resulting in effects). Toxicity endpoints, which are based on studies with active growth, may be overconservative in cases where exposure of PPPs will not co-occur with active macrophyte growth. A comprehensive literature search was performed, using systematic and manual approaches, with the aim of identifying the main active growth period for macrophytes in natural freshwater bodies in climates relevant to the Central and Northern zones of the European Union. The results of the searches were screened initially to identify all potentially relevant references, for which a full evaluation was then performed. Reliability was assessed using the principles of the Klimisch scoring system. As part of the full evaluation, growth periods were identified for each macrophyte species studied. Finally, the extracted growth periods were considered together to determine an overall active growth period for aquatic macrophytes representative of the Central and Northern EU zones. Based on this literature review, the active growth period identified for most aquatic macrophyte species representative of the Central and Northern EU zones is April to September. Relating to the regulatory implication of these results, it may be possible to conclude a low risk for aquatic macrophytes if the predicted surface water exposure period for certain PPPs is demonstrated to be outside the periods of active growth. Integr Environ Assess Manag 2023;00:1-15. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Convergent escape behaviour from distinct visual processing of impending collision in fish and grasshoppers.

In animal species ranging from invertebrate to mammals, visually guided escape behaviours have been studied using looming stimuli, the two-dimensional expanding projection on a screen of an object approaching on a collision course at constant speed. The peak firing rate or membrane potential of neurons responding to looming stimuli often tracks a fixed threshold angular size of the approaching stimulus that contributes to the triggering of escape behaviours. To study whether this result holds more generally, we designed stimuli that simulate acceleration or deceleration over the course of object approach on a collision course. Under these conditions, we found that the angular threshold conveyed by collision detecting neurons in grasshoppers was sensitive to acceleration whereas the triggering of escape behaviours was less so. In contrast, neurons in goldfish identified through the characteristic features of the escape behaviours they trigger, showed little sensitivity to acceleration. This closely mirrored a broader lack of sensitivity to acceleration of the goldfish escape behaviour. Thus, although the sensory coding of simulated colliding stimuli with non-zero acceleration probably differs in grasshoppers and goldfish, the triggering of escape behaviours converges towards similar characteristics. Approaching stimuli with non-zero acceleration may help refine our understanding of neural computations underlying escape behaviours in a broad range of animal species. KEY POINTS: A companion manuscript showed that two mathematical models of collision-detecting neurons in grasshoppers and goldfish make distinct predictions for the timing of their responses to simulated objects approaching on a collision course with non-zero acceleration. Testing these experimental predictions showed that grasshopper neurons are sensitive to acceleration while goldfish neurons are not, in agreement with the distinct models proposed previously in these species using constant velocity approaches. Grasshopper and goldfish escape behaviours occurred after the stimulus reached a fixed angular size insensitive to acceleration, suggesting further downstream processing in grasshopper motor circuits to match what was observed in goldfish. Thus, in spite of different sensory processing in the two species, escape behaviours converge towards similar solutions. The use of object acceleration during approach on a collision course may help better understand the neural computations implemented for collision avoidance in a broad range of species.

Evaluating and Explaining the Variability of Honey Bee Field Studies across Europe Using BEEHAVE.

To assess the effect of plant protection products on pollinator colonies, the higher tier of environmental risk assessment (ERA), for managed honey bee colonies and other pollinators, is in need of a mechanistic effect model. Such models are seen as a promising solution to the shortcomings, which empirical risk assessment can only overcome to a certain degree. A recent assessment of 40 models conducted by the European Food Safety Authority (EFSA) revealed that BEEHAVE is currently the only publicly available mechanistic honey bee model that has the potential to be accepted for ERA purposes. A concern in the use of this model is a lack of model validation against empirical data, spanning field studies conducted in different regions of Europe and covering the variability in colony and environmental conditions. We filled this gap with a BEEHAVE validation study against 66 control colonies of field studies conducted across Germany, Hungary, and the United Kingdom. Our study implements realistic initial colony size and landscape structure to consider foraging options. Overall, the temporal pattern of colony strength is predicted well. Some discrepancies between experimental data and prediction outcomes are explained by assumptions made for model parameterization. Complementary to the recent EFSA study using BEEHAVE, our validation covers a large variability in colony conditions and environmental impacts representing the Northern and Central European Regulatory Zones. Thus we believe that BEEHAVE can be used to serve the development of specific protection goals as well as the development of simulation scenarios for the European Regulatory Zone. Subsequently, the model can be applied as a standard tool for higher tier ERA of managed honey bees using the mechanistic ecotoxicological module for BEEHAVE, BEEHAVEecotox . Environ Toxicol Chem 2023;42:1839-1850. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

A Framework for Algae Modeling in Regulatory Risk Assessment.

The use of toxicokinetic-toxicodynamic (TKTD) modeling in regulatory risk assessment of plant protection products is increasingly popular, especially since the 2018 European Food Safety Authority (EFSA) opinion on TKTD modeling announced that several established models are ready for use in risk assessment. With careful adherence to the guidelines laid out by EFSA, we present a stepwise approach to validation and use of the Simple Algae Model Extended (SAM-X) for regulatory submission in Tier 2C. We demonstrate how the use of moving time windows across time-variable exposure profiles can generate thousands of virtual laboratory mimic simulations that seamlessly predict the effects of time-variable exposures across a full exposure profile while maintaining the laboratory conditions of the standard Organisation for Economic Co-operation and Development (OECD) growth inhibition test. Thus, every virtual laboratory test has a duration of 72 h, with OECD medium and constant light and temperature conditions. The only deviation from the standard test setup is the replacement of constant exposure conditions for time-variable concentrations. The present study demonstrates that for simulation of 72-h toxicity tests, the nutrient dynamics in the SAM-X model are not required, and we propose the alternative use of a simplified model version. For risk assessment, in accordance with the EFSA guidelines we use a median exposure profile of 10 as a threshold, meaning that if a time window within the exposure profile causes 50% growth inhibition when magnified by a factor of 10, the threshold will have been exceeded. We present a simplified example for chlorotoluron and isoproturon. The present case study brings to life our proposed framework for TKTD modeling of algae to establish whether a given exposure can be considered to be of low risk. Environ Toxicol Chem 2023;42:1823-1838. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Approaching object acceleration differentially affects the predictions of neuronal collision avoidance models.

The processing of visual information for collision avoidance has been investigated at the biophysical level in several model systems. In grasshoppers, the (so-called) [Formula: see text] model captures reasonably well the visual processing performed by an identified neuron called the lobular giant movement detector as it tracks approaching objects. Similar phenomenological models have been used to describe either the firing rate or the membrane potential of neurons responsible for visually guided collision avoidance in other animals. Specifically, in goldfish, the [Formula: see text] model has been proposed to describe the Mauthner cell, an identified neuron involved in startle escape responses. In the vinegar fly, a third model was developed for the giant fiber neuron, which triggers last resort escapes immediately before an impending collision. One key property of these models is their prediction that peak neuronal responses occur at a fixed delay after the simulated approaching object reaches a threshold angular size on the retina. This prediction is valid for simulated objects approaching at a constant speed. We tested whether it remains valid when approaching objects accelerate. After characterizing and comparing the models' responses to accelerating and constant speed stimuli, we find that the prediction holds true for the [Formula: see text] and the giant fiber model, but not for the [Formula: see text] model. These results suggest that acceleration in the approach trajectory of an object may help distinguish and further constrain the neuronal computations required for collision avoidance in grasshoppers, fish and vinegar flies.

Physiological Dependency Explains Temperature Differences in Sensitivity Towards Chemical Exposure.

In chemical risk assessment, extrapolations from laboratory tests to more realistic conditions are essential to address the toxic effects of pesticides on individuals and populations under field conditions. To transfer toxicological laboratory tests to differing temperature conditions, or outdoor field scenarios, the consideration of temperature dependence is essential and increases realism. Special consideration is given to the impact of temperature on direct sensitivity of organisms to pesticides, for which there are only few modelling approaches available so far. We present a concept for applying physiological temperature dependencies to toxicokinetic-toxicodynamic (TKTD) parameters in the General Uniformed Threshold model of Survival (GUTS). To test this approach in an exemplary study, temperature dependencies from studies on the developmental rate of the mayfly Cloeon dipterum were applied to the parameters of a previously parameterised TKTD model of this species after exposure to imidacloprid. Using a physiologically derived temperature correction for the TKTD rate constants, model predictions for independently conducted toxicology experiments with temperature ranges between 7.8 and 26.4 °C were performed for validation. Our approach demonstrates the successful transfer of a physiological observed temperature dependency on toxicity parameters and survival patterns for Cloeon dipterum and imidacloprid as a case study.

A generic avian physiologically-based kinetic (PBK) model and its application in three bird species.

Physiologically-based kinetic (PBK) models are effective tools for designing toxicological studies and conducting extrapolations to inform hazard characterization in risk assessment by filling data gaps and defining safe levels of chemicals. In the present work, a generic avian PBK model for male and female birds was developed using PK-Sim and MoBi from the Open Systems Pharmacology Suite (OSPS). The PBK model includes an ovulation model (egg development) to predict concentrations of chemicals in eggs from dietary exposure. The model was parametrized for chicken (Gallus gallus), bobwhite quail (Colinus virginianus) and mallard duck (Anas platyrhynchos) and was tested with nine chemicals for which in vivo studies were available. Time-concentration profiles of chemicals reaching tissues and egg compartment were simulated and compared to in vivo data. The overall accuracy of the PBK model predictions across the analyzed chemicals was good. Model simulations were found to be in the range of 22-79% within a 3-fold and 41-89% were within 10- fold deviation of the in vivo observed data. However, for some compounds scarcity of in-vivo data and inconsistencies between published studies allowed only a limited goodness of fit evaluation. The generic avian PBK model was developed following a "best practice" workflow describing how to build a PBK model for novel species. The credibility and reproducibility of the avian PBK models were scored by evaluation according to the available guidance documents from WHO (2010), and OECD (2021), to increase applicability, confidence and acceptance of these in silico models in chemical risk assessment.

The BEEHAVEecotox Model-Integrating a Mechanistic Effect Module into the Honeybee Colony Model.

Mechanistic effect models are powerful tools for extrapolating from laboratory studies to field conditions. For bees, several good models are available that can simulate colony dynamics. Controlled and reliable experimental systems are also available to estimate the inherent toxicity of pesticides to individuals. However, there is currently no systematic and mechanistic way of linking the output of experimental ecotoxicological testing to bee models for bee risk assessment. We introduce an ecotoxicological module that mechanistically links exposure with the hazard profile of a pesticide for individual honeybees so that colony effects emerge. This mechanistic link allows the translation of results from standard laboratory studies to relevant parameters and processes for simulating bee colony dynamics. The module was integrated into the state-of-the-art honeybee model BEEHAVE. For the integration, BEEHAVE was adapted to mechanistically link the exposure and effects on different cohorts to colony dynamics. The BEEHAVEecotox model was tested against semifield (tunnel) studies, which were deemed the best study type to test whether BEEHAVEecotox predicted realistic effect sizes under controlled conditions. Two pesticides used as toxic standards were chosen for this validation to represent two different modes of action: acute mortality of foragers and chronic brood effects. The ecotoxicological module was able to predict effect sizes in the tunnel studies based on information from standard laboratory tests. In conclusion, the BEEHAVEecotox model is an excellent tool to be used for honeybee risk assessment, interpretation of field and semifield studies, and exploring the efficiency of different mitigation measures. The principles for exposure and effect modules are portable and could be used for any well-constructed honeybee model. Environ Toxicol Chem 2022;41:2870-2882. © 2022 Bayer AG & Sygenta, et al. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

BeeGUTS-A Toxicokinetic-Toxicodynamic Model for the Interpretation and Integration of Acute and Chronic Honey Bee Tests.

Understanding the survival of honey bees after pesticide exposure is key for environmental risk assessment. Currently, effects on adult honey bees are assessed by Organisation for Economic Co-operation and Development standardized guidelines, such as the acute and chronic oral exposure and acute contact exposure tests. The three different tests are interpreted individually, without consideration that the same compound is investigated in the same species, which should allow for an integrative assessment. In the present study we developed, calibrated, and validated a toxicokinetic-toxicodynamic model with 17 existing data sets on acute and chronic effects for honey bees. The model is based on the generalized unified threshold model for survival (GUTS), which is able to integrate the different exposure regimes, taking into account the physiology of the honey bee: the BeeGUTS model. The model is able to accurately describe the effects over time for all three exposure routes combined within one consistent framework. The model can also be used as a validity check for toxicity values used in honey bee risk assessment and to conduct effect assessments for real-life exposure scenarios. This new integrative approach, moving from single-point estimates of toxicity and exposure to a holistic link between exposure and effect, will allow for a higher confidence of honey bee toxicity assessment in the future. Environ Toxicol Chem 2022;41:2193-2201. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Quantitative Morphometric, Physiological, and Metabolic Characteristics of Chickens and Mallards for Physiologically Based Kinetic Model Development.

Physiologically based kinetic (PBK) models are a promising tool for xenobiotic environmental risk assessment that could reduce animal testing by predicting in vivo exposure. PBK models for birds could further our understanding of species-specific sensitivities to xenobiotics, but would require species-specific parameterization. To this end, we summarize multiple major morphometric and physiological characteristics in chickens, particularly laying hens (Gallus gallus) and mallards (Anas platyrhynchos) in a meta-analysis of published data. Where such data did not exist, data are substituted from domesticated ducks (Anas platyrhynchos) and, in their absence, from chickens. The distribution of water between intracellular, extracellular, and plasma is similar in laying hens and mallards. Similarly, the lengths of the components of the small intestine (duodenum, jejunum, and ileum) are similar in chickens and mallards. Moreover, not only are the gastrointestinal absorptive areas similar in mallard and chickens but also they are similar to those in mammals when expressed on a log basis and compared to log body weight. In contrast, the following are much lower in laying hens than mallards: cardiac output (CO), hematocrit (Hct), and blood hemoglobin. There are shifts in ovary weight (increased), oviduct weight (increased), and plasma/serum concentrations of vitellogenin and triglyceride between laying hens and sexually immature females. In contrast, reproductive state does not affect the relative weights of the liver, kidneys, spleen, and gizzard.

Quantitative Comparison of Avian and Mammalian Physiologies for Parameterization of Physiologically Based Kinetic Models.

Physiologically based kinetic (PBK) models facilitate chemical risk assessment by predicting in vivo exposure while reducing the need for animal testing. PBK models for mammals have seen significant progress, which has yet to be achieved for avian systems. Here, we quantitatively compare physiological, metabolic and anatomical characteristics between birds and mammals, with the aim of facilitating bird PBK model development. For some characteristics, there is considerable complementarity between avian and mammalian species with identical values for the following: blood hemoglobin and hemoglobin concentrations per unit erythrocyte volume together with relative weights of the liver, heart, and lungs. There are also systematic differences for some major characteristics between avian and mammalian species including erythrocyte volume, plasma concentrations of albumin, total protein and triglyceride together with liver cell size and relative weights of the kidney, spleen, and ovary. There are also major differences between characteristics between sexually mature and sexually immature female birds. For example, the relative weights of the ovary and oviduct are greater in sexually mature females compared to immature birds as are the plasma concentrations of triglyceride and vitellogenin. Both these sets of differences reflect the genetic "blue print" inherited from ancestral archosaurs such as the production of large eggs with yolk filled oocytes surrounded by egg white proteins, membranes and a calciferous shell together with adaptions for flight in birds or ancestrally in flightless birds.

TWAc-Check: A New Approach to Determine the Appropriate Use of Time-Weighted Average Concentration in Aquatic Risk Assessment.

In pesticide risk assessment, regulatory acceptable concentrations for surface water bodies (RACsw,ch) are used that are derived from standard studies with continuous exposure of organisms to a test compound for days or months. These RACsw,ch are compared with the maximum tested concentration of more realistic exposure scenarios. However, the actual exposure duration could be notably shorter (e.g., hours) than the standard study, which intentionally leads to an overly conservative Tier 1 risk assessment. This discrepancy can be addressed in a risk assessment using the time-weighted average concentration (TWAc). In Europe, the applicability of TWAc for a particular risk assessment is evaluated using a complex decision scheme, which has been controversial; thus we propose an alternative approach: We used TWAc-check (which is based on the idea that the TWAc concept is just a model for aquatic risk assessment) to test whether the use of a TWAc is appropriate for such assessment. The TWAc-check method works by using predicted-measured diagrams to test how well the TWAc model predicts experimental data from peak exposure experiments. Overestimated effects are accepted because the conservatism of the TWAc model is prioritized over the goodness of fit. We illustrate the applicability of TWAc-check by applying it to various data sets for different species and substances. We demonstrate that the applicability is case dependent. Specifically, TWAc-check correctly identifies that the use of TWAc is not appropriate for early onset of effects or delayed effects. The proposed concept shows that the time window is a decisive factor as to whether or not the model is acceptable and that this concept can be used as a potential refinement option prior to the use of toxicokinetic-toxicodynamic models. Environ Toxicol Chem 2022;41:1778-1787. © 2022 Bayer AG. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Disentangling Mechanisms Behind Chronic Lethality through Toxicokinetic-Toxicodynamic Modeling.

Ecotoxicological profiles of the 3 insecticides imidacloprid, thiacloprid, and flupyradifurone in terms of acute and chronic effects were analyzed in Chironomus riparius. Toxicokinetic-toxicodynamic modeling revealed that chironomids would die from starvation as a result of prolonged feeding inhibition under chronic exposures. The starvation effect is an indirect cause for mortality, which, for the neonicotinoids, adds to the direct/acute mortality, although the results suggests that this additional effect is not relevant for flupyradifurone. Environ Toxicol Chem 2021;40:1706-1712. © 2021 Bayer Inc. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

A workflow to build PBTK models for novel species.

Physiology-based pharmacokinetic and toxicokinetic (PBPK/TK) models allow us to simulate the concentration of xenobiotica in the plasma and different tissues of an organism. PBPK/TK models are therefore routinely used in many fields of life sciences to simulate the physiological concentration of exogenous compounds in plasma and tissues. The application of PBTK models in ecotoxicology, however, is currently hampered by the limited availability of models for focal species. Here, we present a best practice workflow that describes how to build PBTK models for novel species. To this end, we extrapolated eight previously established rabbit models for several drugs to six additional mammalian species (human, beagle, rat, monkey, mouse, and minipig). We used established PBTK models for these species to account for the species-specific physiology. The parameter sensitivity in the resulting 56 PBTK models was systematically assessed to rank the relevance of the parameters on overall model performance. Interestingly, more than 80% of the 609 considered model parameters showed a negligible sensitivity throughout all models. Only approximately 5% of all parameters had a high sensitivity in at least one of the PBTK models. This approach allowed us to rank the relevance of the various parameters on overall model performance. We used this information to formulate a best practice guideline for the efficient development of PBTK models for novel animal species. We believe that the workflow proposed in this study will significantly support the development of PBTK models for new animal species in the future.

Towards a spatiotemporally explicit toxicokinetic-toxicodynamic model for earthworm toxicity.

The aim of the environmental risk assessment of chemicals is the prevention of unacceptable adverse effects on the environment. Therefore, the risk assessment for in-soil organisms, such as earthworms, is based on two key elements: the exposure assessment and the effect assessment. In the current risk assessment scheme, these two elements are not linked. While for the exposure assessment, advanced exposure models can take the spatial and temporal scale of substances into account, the effect assessment in the lower tiers considers only a limited temporal and spatial variability. However, for soil organisms, such as earthworms, those scales play a significant role as species move through the soil in response to environmental factors. To overcome this gap, we propose a conceptual integration of pesticide exposure, ecology, and toxicological effects on earthworms using a modular modeling approach. An essential part of this modular approach is the environment module, which utilizes exposure models to provide spatially and temporally explicit information on environmental variables (e.g., temperature, moisture, organic matter content) and chemical concentrations. The behavior module uses this information and simulates the feeding and movement of different earthworm species using a trait-based approach. The resulting exposure can be processed by a toxicokinetic-toxicodynamic (TKTD) module. TKTD models are particularly suitable to make effect predictions for time-variable exposure situations as they include the processes of uptake, elimination, internal distribution, and biotransformation of chemicals and link the internal concentration to an effect at the organism level. The population module incorporates existing population models of different earthworm species. The modular approach is illustrated using a case study with an insecticide. Our results emphasize that using a modular model approach will facilitate the integration of exposure and effects and thus enhance the risk assessment of soil organisms.

Herbicide risk assessments of non-target terrestrial plant communities: A graphical user interface for the plant community model IBC-grass.

Plants located adjacent to agricultural fields are important for maintaining biodiversity in semi-natural landscapes. To avoid undesired impacts on these plants due to herbicide application on the arable fields, regulatory risk assessments are conducted prior to registration to ensure proposed uses of plant protection products do not present an unacceptable risk. The current risk assessment approach for these non-target terrestrial plants (NTTPs) examines impacts at the individual-level as a surrogate approach for protecting the plant community due to the inherent difficulties of directly assessing population or community level impacts. However, modelling approaches are suitable higher tier tools to upscale individual-level effects to community level. IBC-grass is a sophisticated plant community model, which has already been applied in several studies. However, as it is a console application software, it was not deemed sufficiently user-friendly for risk managers and assessors to be conveniently operated without prior expertise in ecological models. Here, we present a user-friendly and open source graphical user interface (GUI) for the application of IBC-grass in regulatory herbicide risk assessment. It facilitates the use of the plant community model for predicting long-term impacts of herbicide applications on NTTP communities. The GUI offers two options to integrate herbicide impacts: (1) dose responses based on current standard experiments (acc. to testing guidelines) and (2) based on specific effect intensities. Both options represent suitable higher tier options for future risk assessments of NTTPs as well as for research on the ecological relevance of effects.