Biocompatibility testing using in vivo tests is often one of the final evaluations of new dental materials. To reduce the likelihood of failure at this late stage, predictive biocompatibility testing using in vitro methods is needed. In this study, we describe a sensitivity analysis of an oral irritation test by evaluating changes in the viability, using the MTT assay, of 3-D models with EpiOral constructs as a case study. Experiments that tested sources of variability in the assay led to recommendations regarding the storage of the constructs after arrival, pipetting procedure, use of MTT reagents from different vendors, use of transepithelial electrical resistance measurements, and statistical analyses. A statistical model was proposed to evaluate whether test substances yield a positive or negative result and the associated statistical confidence. Testing several test compounds such as the Y-4 polymer, that contains a known irritant, and dentally relevant substances such as sodium dodecyl sulfate (SDS) at varying concentrations revealed statistically significant results as expected. Lastly, a software app was designed to support a multiwell culture plate layout design. Overall, the findings and suggestions documented here will support the further development and potential standardization of this assay system and may be useful for the development of other assays using 3-D constructs.
New in vitro methods can support the development of novel dental materials by yielding information about their biocompatibility. In this study, an in vitro oral irritation assay was investigated to better understand what aspects of the method contribute to its variability. There is a potential that such a method could yield similar information to in vivo experiments and reduce animal testing.

Animal-free new approach methods promote chemical assessments based on the comparison between in vitro bioactivity and human internal concentrations, which necessitates a dependable knowledge of human oral bioavailability, i.e., the fraction of an orally ingested chemical that escapes from presystemic (\"first-pass\") metabolic processes and eventually enters systemic circulation. Using a physiologically based toxicokinetic model, we show how human oral bioavailability is impacted by presystemic metabolism within the gut lumen, gut wall, and liver and how this impact differs among chemicals with various permeability and stability properties. Our results highlight the gut lumen as a primary site of presystemic metabolism of certain chemicals, such as di-2-ethylhexyl phthalate (DEHP), for which the gut lumen may even exceed the liver in importance of presystemic metabolism due to these metabolic processes occurring in sequence. For chemicals with low transmembrane permeability and low stability, metabolism within the gut lumen is the most remarkable of the three presystemic metabolic processes. Notably, for chemicals that undergo substantial metabolism within the gut lumen, where the metabolites have high permeability, there is a notable discrepancy between the \"theoretical bioavailability\" (bioavailability of the unchanged parent compound) and the \"apparent bioavailability\" in measurement practices (bioavailability inferred from measured metabolites). Our work highlights the importance of considering presystemic metabolism, notably within the gut lumen, in human exposure and toxicokinetic modeling.

Efforts to use transcriptomics for toxicity testing have classically relied on the assumption that chemicals consistently produce characteristic transcriptomic signatures that are reflective of their mechanism of action. However, the degree to which transcriptomic responses are conserved across different test methodologies has seldom been explored. With increasing regulatory demand for New Approach Methods (NAMs) that use alternatives to animal models and high-content approaches such as transcriptomics, this type of comparative analysis is needed. We examined whether common genes are dysregulated in Japanese quail (Coturnix japonica) liver following sublethal exposure to the flame retardant hexabromocyclododecane (HBCD), when life stage and test methodologies differ. The four exposure scenarios included one NAM: Study 1-early-life stage (ELS) exposure via a single egg injection, and three more traditional approaches; Study 2-adult exposure using a single oral gavage; Study 3-ELS exposure via maternal deposition after adults were exposed through their diet for 7 weeks; and Study 4-ELS exposure via maternal deposition and re-exposure of nestlings through their diet for 17 weeks. The total number of differentially expressed genes (DEGs) detected in each study was variable (Study 1, 550; Study 2, 192; Study 3, 1; Study 4, 3) with only 19 DEGs shared between Studies 1 and 2. Factors contributing to this lack of concordance are discussed and include differences in dose, but also quail strain, exposure route, sampling time, and HBCD stereoisomer composition. The results provide a detailed overview of the transcriptomic responses to HBCD at different life stages and routes of exposure in a model avian species and highlight certain challenges and limits of comparing transcriptomics across different test methodologies. Environ Toxicol Chem 2024;00:1-11. © 2024 The Author(s). Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

The rodent cancer bioassays are conducted for agrochemical safety assessment yet they often do not inform regulatory decision-making. As part of a collaborative effort, the Rethinking Carcinogenicity Assessment for Agrochemicals Project (ReCAAP) developed a reporting framework to guide a weight of evidence (WOE)-based carcinogenicity assessment that demonstrates how to fulfill the regulatory requirements for chronic risk estimation without the need to conduct lifetime rodent bioassays. The framework is the result of a multi-stakeholder collaboration that worked through an iterative process of writing case studies (in the form of waivers), technical peer reviews of waivers, and an incorporation of key learnings back into the framework to be tested in subsequent case study development. The example waivers used to develop the framework were written retrospectively for registered agrochemical active substances for which the necessary data and information could be obtained through risk assessment documents or data evaluation records from the US EPA. This exercise was critical to the development of a framework, but it lacked authenticity in that the stakeholders reviewing the waiver already knew the outcome of the rodent cancer bioassay(s). Syngenta expanded the evaluation of the ReCAAP reporting framework by writing waivers for three prospective case studies for new active substances where the data packages had not yet been submitted for registration. The prospective waivers followed the established framework considering ADME, potential exposure, subchronic toxicity, genotoxicity, immunosuppression, hormone perturbation, mode of action (MOA), and all relevant information available for read-across using a WOE assessment. The point of departure was estimated from the available data, excluding the cancer bioassay results, with a proposed use for the chronic dietary risk assessment. The read-across assessments compared data from reliable registered chemical analogues to strengthen the prediction of chronic toxicity and/or tumorigenic potential. The prospective case studies represent a range of scenarios, from a new molecule in a well-established chemical class with a known MOA to a molecule with a new pesticidal MOA (pMOA) and limited read-across to related molecules. This effort represents an important step in establishing criteria for a WOE-based carcinogenicity assessment without the rodent cancer bioassay(s) while ensuring a health protective chronic dietary risk assessment.

There is global demand for novel ecotoxicity testing tools that are based on alternative to animal models, have high throughput potential, and may be applicable to a wide diversity of taxa. Here we scaled up a microplate-based cell-free neurochemical testing platform to screen 800 putative endocrine disrupting chemicals from the U.S. Environmental Protection Agency\'s ToxCast e1k library against the glutamate (NMDA), muscarinic acetylcholine (mACh), and dopamine (D2) receptors. Each assay was tested in cellular membranes isolated from brain tissues from a representative bird (zebra finch = Taeniopygia castanotis), mammal (mink = Neogale vison), and fish (rainbow trout = Oncorhynchus mykiss). The primary objective of this short communication was to make the results database accessible, while also summarising key attributes of assay performance and presenting some initial observations. In total, 7200 species-chemical-assay combinations were tested, of which 453 combinations were classified as a hit (radioligand binding changed by at least 3 standard deviations). There were some differences across species, and most hits were found for the D2 and NMDA receptors. The most active chemical was C.I. Solvent Yellow 14 followed by Diphenhydramine hydrochloride, Gentian Violet, SR271425, and Zamifenacin. Nine chemicals were tested across multiple plates with a mean relative standard deviation of the specific radioligand binding data being 24.6%. The results demonstrate that cell-free assays may serve as screening tools for large chemical libraries especially for ecological species not easily studied using traditional methods.

Plant protection measures are necessary to prevent pests and diseases from attacking and destroying crop plants and to meet consumer demands for agricultural produce. In the last decades the use of chemical pesticides has largely increased. Farmers are looking for alternatives. Biopesticides should be considered a sustainable solution. They may be less toxic than chemical pesticides, be very specific to the target pest, decompose quickly, and be less likely to cause resistance. On the other hand, lower efficacy and higher costs are two disadvantages of many biopesticides. Biopesticides include macroorganisms, natural compounds and microorganisms. Microbial pesticides are the most widely used and studied class of biopesticides. The greatest difference between microbial and chemical pesticides is the ability of the former to potentially multiply in the environment and on the crop plant after application. The data requirements for the European Union and the United States Environmental Protection Agency are highlighted, as these regulatory processes are the most followed in regions where local regulations for biopesticide products are not available or vague. New Approach Methods already proposed or harmonized for chemical pesticides are presented and discussed with respect to their use in evaluating microbial pesticide formulations. Evaluating the microbials themselves is not as simple as using the same validated New Approach Methods as for synthetic pesticides. Therefore, the authors suggest considering New Approach Method strategies specifically for microbials and global harmonization with acceptability with the advancements of such approaches. Further discussion is needed and greatly appreciated by the experts.

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UNASSIGNED: The U. S. Environmental Protection Agency\'s Endocrine Disruptor Screening Program (EDSP) Tier 1 assays are used to screen for potential endocrine system-disrupting chemicals. A model integrating data from 16 high-throughput screening assays to predict estrogen receptor (ER) agonism has been proposed as an alternative to some low-throughput Tier 1 assays. Later work demonstrated that as few as four assays could replicate the ER agonism predictions from the full model with 98% sensitivity and 92% specificity. The current study utilized chemical clustering to illustrate the coverage of the EDSP Universe of Chemicals (UoC) tested in the existing ER pathway models and to investigate the utility of chemical clustering to evaluate the screening approach using an existing 4-assay model as a test case. Although the full original assay battery is no longer available, the demonstrated contribution of chemical clustering is broadly applicable to assay sets, chemical inventories, and models, and the data analysis used can also be applied to future evaluation of minimal assay models for consideration in screening.
UNASSIGNED: Chemical structures were collected for 6,947 substances via the CompTox Chemicals Dashboard from the over 10,000 UoC and grouped based on structural similarity, generating 826 chemical clusters. Of the 1,812 substances run in the original ER model, 1,730 substances had a single, clearly defined structure. The ER model chemicals with a clearly defined structure that were not present in the EDSP UoC were assigned to chemical clusters using a k-nearest neighbors approach, resulting in 557 EDSP UoC clusters containing at least one ER model chemical.
UNASSIGNED: Performance of an existing 4-assay model in comparison with the existing full ER agonist model was analyzed as related to chemical clustering. This was a case study, and a similar analysis can be performed with any subset model in which the same chemicals (or subset of chemicals) are screened. Of the 365 clusters containing >1 ER model chemical, 321 did not have any chemicals predicted to be agonists by the full ER agonist model. The best 4-assay subset ER agonist model disagreed with the full ER agonist model by predicting agonist activity for 122 chemicals from 91 of the 321 clusters. There were 44 clusters with at least two chemicals and at least one agonist based upon the full ER agonist model, which allowed accuracy predictions on a per-cluster basis. The accuracy of the best 4-assay subset ER agonist model ranged from 50% to 100% across these 44 clusters, with 32 clusters having accuracy ≥90%. Overall, the best 4-assay subset ER agonist model resulted in 122 false-positive and only 2 false-negative predictions compared with the full ER agonist model. Most false positives (89) were active in only two of the four assays, whereas all but 11 true positive chemicals were active in at least three assays. False positive chemicals also tended to have lower area under the curve (AUC) values, with 110 out of 122 false positives having an AUC value below 0.214, which is lower than 75% of the positives as predicted by the full ER agonist model. Many false positives demonstrated borderline activity. The median AUC value for the 122 false positives from the best 4-assay subset ER agonist model was 0.138, whereas the threshold for an active prediction is 0.1.
UNASSIGNED: Our results show that the existing 4-assay model performs well across a range of structurally diverse chemicals. Although this is a descriptive analysis of previous results, several concepts can be applied to any screening model used in the future. First, the clustering of the chemicals provides a means of ensuring that future screening evaluations consider the broad chemical space represented by the EDSP UoC. The clusters can also assist in prioritizing future chemicals for screening in specific clusters based on the activity of known chemicals in those clusters. The clustering approach can be useful in providing a framework to evaluate which portions of the EDSP UoC chemical space are reliably covered by in silico and in vitro approaches and where predictions from either method alone or both methods combined are most reliable. The lessons learned from this case study can be easily applied to future evaluations of model applicability and screening to evaluate future datasets.

Bacillus cereus (Bc) is a wide group of Gram-positive and spore-forming bacteria, known to be the etiological agents of various human infections, primarily food poisoning. The Bc group includes enteropathogenic strains able to germinate in the digestive tract and to produce enterotoxins such as Nhe, Hbl, and CytK. One species of the group, Bacillus thuringiensis (Bt), has the unique feature of producing insecticidal crystals during sporulation, making it an important alternative to chemical pesticides to protect crops from insect pest larvae. Nevertheless, several studies have suggested a link between the ingestion of pesticide strains and human cases of food poisoning, calling their safety into question. Consequently, reliable tools for virulence assessment are worth developing to aid decision making in pesticide regulation. Here, we propose complementary approaches based on two biological models, the human intestinal Caco-2 cell line and the insect Drosophila melanogaster, to assess and rank the enteric virulence potency of Bt strains in comparison with other Bc group members. Using a dataset of 48 Bacillus spp. strains, we showed that some Bc group strains, including Bt, were able to induce cytotoxicity in Caco-2 cells with concomitant release of IL-8 cytokine, a landmark of pro-inflammatory response. In the D. melanogaster model, we were able to sort a panel of 39 strains into four different classes of virulence, ranging from no virulence to strong virulence. Importantly, for the most virulent strains, mortality was associated with a loss of intestinal barrier integrity. Interestingly, although strains can share a common toxinotype, they display different degrees of virulence, suggesting the existence of specific mechanisms of virulence expression in vivo in the intestine.

Endocrine disruptors (EDs) pose a serious threat to human health and the environment and require a comprehensive evaluation to be identified. The identification of EDs require a substantial amount of data, both in vitro and in vivo, due to the current scientific criteria in the EU. At the same time, the EU strives to reduce animal testing due to concerns regarding animal welfare and sensitivity of animal studies to adequately detect adverse effects relevant for human health. Perfluorooctane sulfonic acid (PFOS) is a persistent organic pollutant that is suspected to be an ED based on academic research, however it is not identified as such from a regulatory perspective. It has previously been shown that PFOS has the potential to cause neurotoxicity as well as affect the thyroid system, and it is known that specific thyroid hormone levels are critical in the development of the brain during. In this work, the aim was to evaluate a mechanism-based approach to identify ED properties of PFOS based on the Adverse Outcome Pathway (AOP) framework and using New Approach Methods (NAMs), by comparing this approach to an ED assessment based on the currently available guidance document. An AOP network (AOPN) was generated for the thyroid modality, and AOPs leading to developmental neurotoxicity (DNT) were identified. A literature search and screening process based on the AOPN, and systematic review methodology, was performed, followed by a rigorous Weight-of-Evidence (WoE) assessment. Evidence was mapped back onto the AOPN used for the literature search, to identify possible endocrine Modes-of-Action (MoAs) for PFOS and data gaps in the two assessments. It could be concluded that PFOS fulfils the criteria for ED classification in the standard ED assessment, but not in the mechanism-based assessment. The need for quantitative information, such as quantitative AOPs, for the mechanism-based approach is discussed. The possibility of a directly neurotoxic alternative MoA was also highlighted based on available in vitro data. Opportunities and challenges with implementing AOPs and NAMs into the regulatory assessment of EDs, and assessing hazard in the Next Generation Risk Assessment, is discussed. This case study exploring the mechanism-based approach to ED identification represents an important step toward more accurate and predictive assessment of EDs based on AOPs and NAMs, and to the Next Generation Risk Assessment (NGRA) concept.