Advancing Ecotoxicological Studies: Utilizing New Approach Methodologies to Enable Cross-Species Extrapolation and Reduce Avian Testing.

Ecological risk assessments of agrochemicals have traditionally depended on in vivo guideline tests using northern bobwhite and mallard to provide relevant endpoints for avian species. However, these studies have limitations, including animal welfare concerns, the time and cost involved, limited potential for extrapolation to more realistic exposure conditions, and the lack of mechanistic understanding. The proof-of-concept work presented a case study for thiamethoxam in three avian species, demonstrating the potential of physiologically based kinetic (PBK) modeling to enable dosimetry extrapolations that inform hazard characterization in risk assessment, and reduce the use of avian testing. The model structure for northern bobwhite and mallard contained ten compartments, while an additional ovulation model was included for chicken in the physiological state of egg-laying. The model was first parameterized and evaluated for chicken and northern bobwhite using in vitro kinetic measurements and in vivo toxicokinetic (TK) data. The chicken model was then extrapolated to mallard based on allometric scaling. The models were then used to map the TK profiles across species by simulating internal dose metrics in different avian toxicology studies. These metrics, including peak blood concentrations (Cmax) and area under the curve (AUC) for blood concentration, were determined for acute, subacute, or chronic toxicity endpoints for mallard and northern bobwhite, enabling a quantitative cross-species and cross-route comparison of dosimetry. The results suggested that the chronic toxicological response of birds exposed to thiamethoxam is highly dependent on internal exposure, while mallard appeared to be more dynamically sensitive to thiamethoxam on an acute oral exposure basis. The case study increases the confidence in using new approach methodologies (NAMs) for interpreting avian toxicity studies and facilitating in vitro-in silico-based ecological risk assessments of agrochemicals.

Data derived extrapolation factors (DDEFs) for rat to human interspecies extrapolation for the HPPD inhibitor mesotrione.

In the risk assessment of agrochemicals, there has been a historical paucity of using data to refine the default adjustment factors, even though large datasets are available to support this. The current state of the science for addressing uncertainty regarding animal to human extrapolation (AFA) is to develop a "data-derived" adjustment factor (DDEF) to quantify such differences, if data are available. Toxicokinetic (TK) and toxicodynamic (TD) differences between species can be utilized for the DDEF, with human datasets being ideal yet rare. We identified a case for a currently registered herbicide, mesotrione, in which human TK and TD are available. This case study outlines an approach for the development of DDEFs using comparative human and animal data and based on an adverse outcome pathway (AOP) for inhibition of 4-hydroxyphenol pyruvate dioxygenase (HHPD). The calculated DDEF for rat to human extrapolation (AFA) for kinetics (AFAK = 2.5) was multiplied by the AFA for dynamics (AFAD = 0.3) resulting in a composite DDEF of ∼1 (AFA = 0.75). This reflects the AOP and available scientific evidence that humans are less sensitive than rats to the effects of HPPD inhibitors. Further analyses were conducted utilizing in vitro datasets from hepatocytes and liver cytosols and extrapolated to whole animal using in vitro to in vivo extrapolation (IVIVE) to support toxicodynamic extrapolation. The in vitro datasets resulted in the same AFAD as derived for in vivo data (AFAD = 0.3). These analyses demonstrate that a majority of the species differences are related to toxicodynamics. Future work with additional in vitro/in vivo datasets for other HPPD inhibitors and cell types will further support this result. This work demonstrates utilization of all available toxicokinetic and toxicodynamic data to replace default uncertainty factors for agrochemical human health risk assessment.

Physiologically based kinetic (PBK) modeling of propiconazole using a machine learning-enhanced read-across approach for interspecies extrapolation.

A significant challenge in the traditional human health risk assessment of agrochemicals is the uncertainty in quantifying the interspecies differences between animal models and humans. To work toward a more accurate and animal-free risk determination, new approaches such as physiologically based kinetic (PBK) modeling have been used to perform dosimetry extrapolation from animals to humans. However, the regulatory use and acceptance of PBK modeling is limited for chemicals that lack in vivo animal pharmacokinetic (PK) data, given the inability to evaluate models. To address these challenges, this study developed PBK models in the absence of in vivo PK data for the fungicide propiconazole, an activator of constitutive androstane receptor (CAR)/pregnane X receptor (PXR). A fit-for-purpose read-across approach was integrated with hierarchical clustering - an unsupervised machine learning algorithm, to bridge the knowledge gap. The integration allowed the incorporation of a broad spectrum of attributes for analog consideration, and enabled the analog selection in a simple, reproducible, and objective manner. The applicability was evaluated and demonstrated using penconazole (source) and three pseudo-unknown target chemicals (epoxiconazole, tebuconazole and triadimefon). Applying this machine learning-enhanced read-across approach, difenoconazole was selected as the most appropriate analog for propiconazole. A mouse PBK model was developed and evaluated for difenoconazole (source), with the mode of action of CAR/PXR activation incorporated to simulate the in vivo autoinduction of metabolism. The difenoconazole mouse model then served as a template for constructing the propiconazole mouse model. A parallelogram approach was subsequently applied to develop the propiconazole rat and human models, enabling a quantitative assessment of interspecies differences in dosimetry. This integrated approach represents a substantial advancement toward refining risk assessment of propiconazole within the framework of animal alternative safety assessment strategies.

USP18 Antagonizes Pyroptosis by Facilitating Selective Autophagic Degradation of Gasdermin D.

As a key executioner of pyroptosis, Gasdermin D (GSDMD) plays a crucial role in host defense and emerges as an essential therapeutic target in the treatment of inflammatory diseases. So far, the understanding of the mechanisms that regulate the protein level of GSDMD to prevent detrimental effects and maintain homeostasis is currently limited. Here, we unveil that ubiquitin-specific peptidase 18 (USP18) works as a negative regulator of pyroptosis by targeting GSDMD for degradation and preventing excessive innate immune responses. Mechanically, USP18 recruits E3 ubiquitin ligase mind bomb homolog 2 (MIB2) to catalyze ubiquitination on GSDMD at lysine (K) 168, which acts as a recognition signal for the selective autophagic degradation of GSDMD. We further confirm the alleviating effect of USP18 on LPS-triggered inflammation in vivo. Collectively, our study demonstrates the role of USP18 in regulating GSDMD-mediated pyroptosis and reveals a previously unknown mechanism by which GSDMD protein level is rigorously controlled by selective autophagy.

Moso bamboo (Phyllostachys edulis) expansion enhances soil pH and alters soil nutrients and microbial communities.

Amid global environmental concerns, the issue of bamboo expansion has garnered significant attention due to its extensive and profound impacts on the ecosystems. Bamboo expansion occurs in native and introduced habitats worldwide, particularly in Asia. However, the effects of bamboo expansion on soil pH, nutrient levels, and microbial communities are complex and vary across different environments. To address this knowledge gap, we conducted a meta-analysis with 2037 paired observations from 81 studies. The results showed that soil pH increased by 6.99 % (0-20 cm) and 4.49 % (20-40 cm) after bamboo expansion. Notably, soil pH increased more in the coniferous forest with bamboo expansion than in the broadleaf forest. Soil pH progressively increased over time since the establishment of bamboo stands. The extent of soil pH elevation was significantly positively correlated with the proportion of bamboo within the forest stand and mean annual solar radiation. In contrast, it was significantly negatively correlated with the mean annual temperature. The elevation of pH is closely related to expansion stage and expanded forest type rather than primarily shaped by climatic factors across a large scale. We also found that bamboo expansion into coniferous forests brought about a notable 14.14 % reduction in total nitrogen (TN). Varied expansion stages resulted in TN reductions of 6.88 % and 7.99 % for mixed forests and bamboo stands, respectively, compared to native forests. Pure bamboo stands exhibited a remarkable 30.39 % increase in ammonium nitrogen and a significant 21.12 % decrease in nitrate nitrogen compared to their native counterparts. Furthermore, bamboo expansion contributed to heightened soil fungal diversity. Taken together, our findings highlight that bamboo expansion leads to an increase in soil pH and alters soil N components and fungal microbial communities, providing valuable insights for future ecological conservation and resource management.