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An understanding of the combined effects of climate change (CC) and other anthropogenic stressors, such as chemical exposures, is essential for improving ecological risk assessments of vulnerable ecosystems. In the Great Barrier Reef, coral reefs are under increasingly severe duress from increasing ocean temperatures, acidification, and cyclone intensities associated with CC. In addition to these stressors, inshore reef systems, such as the Mackay-Whitsunday coastal zone, are being impacted by other anthropogenic stressors, including chemical, nutrient, and sediment exposures related to more intense rainfall events that increase the catchment runoff of contaminated waters. To illustrate an approach for incorporating CC into ecological risk assessment frameworks, we developed an adverse outcome pathway network to conceptually delineate the effects of climate variables and photosystem II herbicide (diuron) exposures on scleractinian corals. This informed the development of a Bayesian network (BN) to quantitatively compare the effects of historical (1975-2005) and future projected climate on inshore hard coral bleaching, mortality, and cover. This BN demonstrated how risk may be predicted for multiple physical and biological stressors, including temperature, ocean acidification, cyclones, sediments, macroalgae competition, and crown of thorns starfish predation, as well as chemical stressors such as nitrogen and herbicides. Climate scenarios included an ensemble of 16 downscaled models encompassing current and future conditions based on multiple emission scenarios for two 30-year periods. It was found that both climate-related and catchment-related stressors pose a risk to these inshore reef systems, with projected increases in coral bleaching and coral mortality under all future climate scenarios. This modeling exercise can support the identification of risk drivers for the prioritization of management interventions to build future resilient reefs. Integr Environ Assess Manag 2024;20:401-418. © 2023 Norwegian Institute for Water Research and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA., (© 2023 Norwegian Institute for Water Research and The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.)

Global climate change will significantly impact the biodiversity of freshwater ecosystems, both directly and indirectly via the exacerbation of impacts from other stressors. Pesticides form a prime example of chemical stressors that are expected to synergize with climate change. Aquatic exposures to pesticides might change in magnitude due to increased runoff from agricultural fields, and in composition, as application patterns will change due to changes in pest pressures and crop types. Any prospective chemical risk assessment that aims to capture the influence of climate change should properly and comprehensively account for the variabilities and uncertainties that are inherent to projections of future climate. This is only feasible if they probabilistically propagate extensive ensembles of climate model projections. However, current prospective risk assessments typically make use of process-based models of chemical fate that do not typically allow for such high-throughput applications. Here, we describe a Bayesian network model that does. It incorporates a two-step univariate regression model based on a 30-day antecedent precipitation index, circumventing the need for computationally laborious mechanistic models. We show its feasibility and application potential in a case study with two pesticides in a Norwegian stream: the fungicide trifloxystrobin and herbicide clopyralid. Our analysis showed that variations in pesticide application rates as well as precipitation intensity lead to variations in in-stream exposures. When relating to aquatic risks, the influence of these processes is reduced and distributions of risk are dominated by effect-related parameters. Predicted risks for clopyralid were negligible, but the probability of unacceptable future environmental risks due to exposure to trifloxystrobin (i.e., a risk quotient >1) was 8%-12%. This percentage further increased to 30%-35% when a more conservative precautionary factor of 100 instead of 30 was used. Integr Environ Assess Manag 2024;20:384-400. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)., (© 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).)

The Society of Environmental Toxicology and Chemistry (SETAC) convened a Pellston workshop in 2022 to examine how information on climate change could be better incorporated into the ecological risk assessment (ERA) process for chemicals as well as other environmental stressors. A major impetus for this workshop is that climate change can affect components of ecological risks in multiple direct and indirect ways, including the use patterns and environmental exposure pathways of chemical stressors such as pesticides, the toxicity of chemicals in receiving environments, and the vulnerability of species of concern related to habitat quality and use. This article explores a modeling approach for integrating climate model projections into the assessment of near- and long-term ecological risks, developed in collaboration with climate scientists. State-of-the-art global climate modeling and downscaling techniques may enable climate projections at scales appropriate for the study area. It is, however, also important to realize the limitations of individual global climate models and make use of climate model ensembles represented by statistical properties. Here, we present a probabilistic modeling approach aiming to combine projected climatic variables as well as the associated uncertainties from climate model ensembles in conjunction with ERA pathways. We draw upon three examples of ERA that utilized Bayesian networks for this purpose and that also represent methodological advancements for better prediction of future risks to ecosystems. We envision that the modeling approach developed from this international collaboration will contribute to better assessment and management of risks from chemical stressors in a changing climate. Integr Environ Assess Manag 2024;20:367-383. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)., (© 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).)

Bayesian network (BN) models are increasingly used as tools to support probabilistic environmental risk assessments (ERAs), because they can better account for uncertainty compared with the simpler approaches commonly used in traditional ERA. We used BNs as metamodels to link various sources of information in a probabilistic framework, to predict the risk of pesticides to aquatic communities under given scenarios. The research focused on rice fields surrounding the Albufera Natural Park (Valencia, Spain), and considered three selected pesticides: acetamiprid (an insecticide), 2-methyl-4-chlorophenoxyacetic acid (MCPA; a herbicide), and azoxystrobin (a fungicide). The developed BN linked the inputs and outputs of two pesticide models: a process-based exposure model (Rice Water Quality [RICEWQ]), and a probabilistic effects model (Predicts the Ecological Risk of Pesticides [PERPEST]) using case-based reasoning with data from microcosm and mesocosm experiments. The model characterized risk at three levels in a hierarchy: biological endpoints (e.g., molluscs, zooplankton, insects, etc.), endpoint groups (plants, invertebrates, vertebrates, and community processes), and community. The pesticide risk to a biological endpoint was characterized as the probability of an effect for a given pesticide concentration interval. The risk to an endpoint group was calculated as the joint probability of effect on any of the endpoints in the group. Likewise, community-level risk was calculated as the joint probability of any of the endpoint groups being affected. This approach enabled comparison of risk to endpoint groups across different pesticide types. For example, in a scenario for the year 2050, the predicted risk of the insecticide to the community (40% probability of effect) was dominated by the risk to invertebrates (36% risk). In contrast, herbicide-related risk to the community (63%) resulted from risk to both plants (35%) and invertebrates (38%); the latter might represent (in the present study) indirect effects of toxicity through the food chain. This novel approach combines the quantification of spatial variability of exposure with probabilistic risk prediction for different components of aquatic ecosystems. Environ Toxicol Chem 2024;43:182-196. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC., (© 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.)

Pollution by agricultural pesticides is one of the most important pressures affecting Mediterranean coastal wetlands. Pesticide risks are expected to be influenced by climate change, which will result in an increase of temperatures and a decrease in annual precipitation. On the other hand, pesticide dosages are expected to change given the increase in pest resistance and the implementation of environmental policies like the European ´Farm-to-Fork` strategy, which aims for a 50 % reduction in pesticide usage by 2030. The influence of climate change and pesticide use practices on the ecological risks of pesticides needs to be evaluated making use of realistic environmental scenarios. This study investigates how different climate change and pesticide use practices affect the ecological risks of pesticides in the Albufera Natural Park (Valencia, Spain), a protected Mediterranean coastal wetland. We performed a probabilistic risk assessment for nine pesticides applied in rice production using three climatic scenarios (for the years 2008, 2050 and 2100), three pesticide dosage regimes (the recommended dose, and 50 % increase and 50 % decrease), and their combinations. The scenarios were used to simulate pesticide exposure concentrations in the water column of the rice paddies using the RICEWQ model. Pesticide effects were characterized using acute and chronic Species Sensitivity Distributions built with toxicity data for aquatic organisms. Risk quotients were calculated as probability distributions making use of Bayesian networks. Our results show that future climate projections will influence exposure concentrations for some of the studied pesticides, yielding higher dissipation and lower exposure in scenarios dominated by an increase of temperatures, and higher exposure peaks in scenarios where heavy precipitation events occur right after pesticide application. Our case study shows that pesticides such as azoxystrobin, difenoconazole and MCPA are posing unacceptable ecological risks for aquatic organisms, and that the implementation of the ´Farm-to-Fork` strategy is crucial to reduce them., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Conventional environmental risk assessment of chemicals is based on a calculated risk quotient, representing the ratio of exposure to effects of the chemical, in combination with assessment factors to account for uncertainty. Probabilistic risk assessment approaches can offer more transparency by using probability distributions for exposure and/or effects to account for variability and uncertainty. In this study, a probabilistic approach using Bayesian network modeling is explored as an alternative to traditional risk calculation. Bayesian networks can serve as meta-models that link information from several sources and offer a transparent way of incorporating the required characterization of uncertainty for environmental risk assessment. To this end, a Bayesian network has been developed and parameterized for the pesticides azoxystrobin, metribuzin, and imidacloprid. We illustrate the development from deterministic (traditional) risk calculation, via intermediate versions, to fully probabilistic risk characterization using azoxystrobin as an example. We also demonstrate the seasonal risk calculation for the three pesticides. Integr Environ Assess Manag 2022;18:1072-1087. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)., (© 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).)

By 2050, the global population is predicted to reach nine billion, with almost three quarters living in cities. The road to 2050 will be marked by changes in land use, climate, and the management of water and food across the world. These global changes (GCs) will likely affect the emissions, transport, and fate of chemicals, and thus the exposure of the natural environment to chemicals. ECORISK2050 is a Marie Skłodowska-Curie Innovative Training Network that brings together an interdisciplinary consortium of academic, industry and governmental partners to deliver a new generation of scientists, with the skills required to study and manage the effects of GCs on chemical risks to the aquatic environment. The research and training goals are to: (1) assess how inputs and behaviour of chemicals from agriculture and urban environments are affected by different environmental conditions, and how different GC scenarios will drive changes in chemical risks to human and ecosystem health; (2) identify short-to-medium term adaptation and mitigation strategies, to abate unacceptable increases to risks, and (3) develop tools for use by industry and policymakers for the assessment and management of the impacts of GC-related drivers on chemical risks. This project will deliver the next generation of scientists, consultants, and industry and governmental decision-makers who have the knowledge and skillsets required to address the changing pressures associated with chemicals emitted by agricultural and urban activities, on aquatic systems on the path to 2050 and beyond., Competing Interests: No competing interests were disclosed., (Copyright: © 2022 Welch SA et al.)

Background: Podocytes play an important role in the development of proteinuria and focal glomerulosclerosis. Previously we have demonstrated that a combination of two monoclonal antibodies (mAb) against aminopeptidase A (APA), an enzyme present on podocytes, induces a massive acute albuminuria in mice. The present study examined the relationship between the acute antibody-induced albuminuria and the development of focal glomerulosclerosis in the Thy-1.1 transgenic mouse. This mouse expresses a hybrid human-mouse Thy-1.1 antigen on the podocytes, and slowly but spontaneously develops albuminuria and focal glomerulosclerosis., Methods: Five-week-old non-albuminuric Thy-1.1 transgenic and non-transgenic control mice were injected with anti-APA and anti-Thy-1.1 mAb or saline. Albuminuria was measured at days 1, 7, 14 and 21. At day 21 kidneys were processed for light microscopy, immunofluorescence, and electron microscopy., Results: Injection of anti-APA and anti-Thy1.1 mAb in Thy-1.1 transgenic mice induced an albuminuria at day 1 that persisted at day 21. The acute albuminuria after injection of anti-APA mAb was more prominent but transient in non-transgenic mice. In non-trangenic mice no albuminuria could be induced with anti-Thy 1.1 mAb. Light microscopy revealed normal glomeruli at day 1 in all transgenic mice, however, at day 21 advanced glomerulosclerotic lesions were seen in mice injected with either anti-APA mAb (37+/-19% of glomeruli affected) or anti-Thy-1.1 mAb (71+/-5%). Non-transgenic mice did not reveal sclerotic lesions at any time investigated. In the transgenic mice the percentage of focal glomerulosclerosis at day 21 did not correlate with albuminuria at day 21. However, we found a highly significant correlation between percentage of focal glomerulosclerosis and the time-averaged albuminuria over the three-week study period (P < 0.001)., Conclusion: Injection of a combination of anti-APA or anti-Thy-1.1 mAb into one mo old, non-albuminuric Thy-1.1 transgenic mice induces an acute albuminuria at day 1 that is accompanied by an accelerated focal glomerulosclerosis at day 21. We suggest that the Thy-1.1 transgenic mouse is an excellent model to study specifically the relation between podocytic injury, albuminuria and the development of focal glomerulosclerosis.

It has been shown that injection of combinations of anti-aminopeptidase A (APA) monoclonal antibodies (mAb) that inhibit the enzyme activity induces an acute albuminuria in mice. This albuminuria is not dependent on inflammatory cells, complement, or the coagulation system. APA is an important regulator of the renin-angiotensin system because it is involved in the degradation of angiotensin II (Ang II). This study examined the potential role of glomerular Ang II in the induction of albuminuria. The relation among renal Ang II, glomerular APAX enzyme activity, and albuminuria was examined first. Injection of the nephritogenic combinations ASD-3/37 and ASD-37/41 in BALB/c mice induced albuminuria, whereas the non-nephritogenic combination ASD-3/41 had no effect. There was no clear relation between the inhibition of glomerular APA activity and albuminuria, yet it was evident that intrarenal Ang II levels were significantly increased in albuminuric mice and not in nonalbuminuric mice. As a next step, anti-APA mAb were administered to angiotensinogen-deficient mice that do not produce Ang II, and kidney morphology and albuminuria were determined. Angiotensinogen-deficient mice also developed albuminuria upon ASD-37/41 administration. Altogether, these findings clearly demonstrate that Ang II is not required for the induction of albuminuria upon injection of enzyme-inhibiting anti-APA mAb.

Background: Aminopeptidase A is an enzyme that is present on podocytes and is involved in the degradation of angiotensin II. In previous studies in mice, we administered single monoclonal antibodies directed against aminopeptidase A. We observed that only monoclonal antibodies that inhibited aminopeptidase A enzyme activity caused albuminuria., Methods: In this study, the effects of the combined injections of two monoclonal anti-aminopeptidase A antibodies (mAbs) were studied, using a combination of anti-aminopeptidase A mAbs that were directed against two different domains involved in the aminopeptidase A enzyme activity (ASD-3 or ASD-37) and an anti-aminopeptidase A mAb not related to the enzyme active site (ASD-41)., Results: An injection of the combinations ASD-3/37 (total 4 mg, 1:1 ratio) and ASD-37/41 (total 4 mg, 1:1 ratio) in doses that do not cause albuminuria when given alone (4 mg) induced massive albuminuria at day 1 after injection. The combination ASD-3/41 had no effect. This albuminuria was not dependent on systemic immune mediators of inflammation and could not merely be related to a blockade of aminopeptidase A enzyme activity. However, a correlation was observed between the induction of albuminuria and the aggregation of the mAbs injected and aminopeptidase A on the podocytes. An injection of the combinations ASD-3/37 or ASD-37/41 did not cause an increase in systemic blood pressure. The treatment with a combination of enalapril and losartan lowered blood pressure (53 +/- 10 vs. 90 +/- 3 mm Hg in untreated mice) and reduced the acute albuminuria by 55% (11,145 +/- 864 vs. 24,517 +/- 2448 micrograms albumin/18 hr in untreated mice). However, similar effects were observed using triple therapy. Therefore, the reduction of albuminuria by the combined treatment of enalapril/losartan seems to be the consequence of the reduction in the systemic blood pressure. These findings argue against a specific role for angiotensin II in this model., Conclusions: The combined injection of two mAbs directed against different domains of aminopeptidase A induces a massive albuminuria in mice, which is not merely dependent on angiotensin II. We hypothesize that the direct binding of mAbs to at least two pathogenic domains on aminopeptidase A triggers the podocyte to release mediators that are involved in the observed albuminuria.

The muscle-myosin heavy-chain (mMHC) gene of Drosophila hydei has been sequenced completely (size 23.3 kb). The sequence comparison with the D. melanogaster mMHC gene revealed that the exon-intron pattern is identical. The protein coding regions show a high degree of conservation (97%). The alternatively spliced exons (3a-b, 7a-d, 9a-c, 11a-e, and 15a-b) display more variations in the number of nonsynonymous and synonymous substitutions than the common exons (2, 4, 5, 6, 8, 10, 12, 13, 14, 16, 17, and 19). The base composition at synonymous sites of fourfold degenerate codons (third position) is not biased in the alternative exons. In the common exons there exists a bias for C and against A. These findings imply that the alternative exons of the Drosophila mMHC gene evolve at a different, in several cases higher, rate than the common ones. The 5' splice junctions and 5' and 3' untranslated regions show a high level of similarity, indicating a functional constraint on these sequences. The intron regions vary considerably in length within one species, but the corresponding introns are very similar in length between the two species and all contain stretches of sequence similarity. A particular example is the first intron, which contains multiple regions of similarity. In the conserved regions of intron 12 (head-tail border) sequences were found which have the potential to direct another smaller mMHC transcript.

SDS-PAGE of affinity-purified APA under reducing conditions showed in addition to the specific APA band of M(r) 130 kD, a second band of M(r) 43 kD. Internal amino acid sequencing of three tryptic peptides from this second band, that was cut out of the polyacrylamide gel, matched the actin sequence. The identity of the 43 kD band was also confirmed by Western blotting.