Modeling ferroptosis in human dopaminergic neurons: Pitfalls and opportunities for neurodegeneration research.

The activation of ferroptosis is being pursued in cancer research as a strategy to target apoptosis-resistant cells. By contrast, in various diseases that affect the cardiovascular system, kidneys, liver, and central and peripheral nervous systems, attention is directed toward interventions that prevent ferroptotic cell death. Mechanistic insights into both research areas stem largely from studies using cellular in vitro models. However, intervention strategies that show promise in cellular test systems often fail in clinical trials, which raises concerns regarding the predictive validity of the utilized in vitro models. In this study, the human LUHMES cell line, which serves as a model for human dopaminergic neurons, was used to characterize factors influencing the activation of ferroptosis. Erastin and RSL-3 induced cell death that was distinct from apoptosis. Parameters such as the differentiation state of LUHMES cells, cell density, and the number and timing of medium changes were identified as determinants of sensitivity to ferroptosis activation. In differentiated LUHMES cells, interventions at mechanistically divergent sites (iron chelation, coenzyme Q10, peroxidase mimics, or inhibition of 12/15-lipoxygenase) provide almost complete protection from ferroptosis. LUHMES cells allowed the experimental modulation of intracellular iron concentrations and demonstrated a correlation between intracellular iron levels, the rate of lipid peroxidation, as well as the sensitivity of the cells to ferroptotic cell death. These findings underscore the importance of understanding the various factors that influence ferroptosis activation and highlight the need for well-characterized in vitro models to enhance the reliability and predictive value of observations in ferroptosis research, particularly when translating findings into in vivo contexts.

Elements and development processes for test methods in toxicology and human health-relevant life science research.

Many laboratory procedures generate data on properties of chemicals, but they cannot be equated with toxicological "test methods". This apparent discrepancy is not limited to in vitro testing, using animal-free new approach methods (NAM), but also applies to animal-based testing approaches. Here, we give a brief overview of the differences between data generation and the setup or use of a complete test method. While there is excellent literature available on this topic for specialists (GIVIMP guidance; ToxTemp overview), a brief overview and easily-accessible entry point may be useful for a broader community. We provide a single figure to summarize all test method elements and processes required in the development (setup and adaptation) of a test method. The exposure scheme, the endpoint, and the test system are briefly outlined as fundamental elements of any test method. A rationale is provided, why they are not sufficient. We then explain the importance and role of purpose definition (including some information on what is modelled) and the prediction model, aka data interpretation procedure, which depends on the purpose definition, as further essential elements. This connection exemplifies that all fundamental elements are interdependent, and none can be omitted. Finally, discussion is provided on validation as a measure to provide confidence in the reliability, performance, and relevance of a test method. In this sense, validation may be considered a sixth fundamental element for practical use of test methods.

Many laboratory procedures generate data on chemicals, but they cannot be considered complete toxicological "test methods". Here, we give a brief explanation of the fundamental elements of a toxicological test method. We provide an illustration that gives a complete overview of the devel­opment of a test method for non-specialists. We introduce the six fundamental elements, i.e., the exposure scheme, the test endpoint, the test system, the purpose definition and the prediction model and describe how they work together. Finally, we discuss the concept of validation. An understanding of these concepts is important for good-quality scientific research and especially for the development and acceptance of alternatives to animal experiments.

Structural Insights into Neonicotinoids and N-Unsubstituted Metabolites on Human nAChRs by Molecular Docking, Dynamics Simulations, and Calcium Imaging.

Neonicotinoid pesticides were initially designed in order to achieve species selectivity on insect nicotinic acetylcholine receptors (nAChRs). However, concerns arose when agonistic effects were also detected in human cells expressing nAChRs. In the context of next-generation risk assessments (NGRAs), new approach methods (NAMs) should replace animal testing where appropriate. Herein, we present a combination of in silico and in vitro methodologies that are used to investigate the potentially toxic effects of neonicotinoids and nicotinoid metabolites on human neurons. First, an ensemble docking study was conducted on the nAChR isoforms α7 and α3ß4 to assess potential crucial molecular initiating event (MIE) interactions. Representative docking poses were further refined using molecular dynamics (MD) simulations and binding energy calculations using implicit solvent models. Finally, calcium imaging on LUHMES neurons confirmed a key event (KE) downstream of the MIE. This method was also used to confirm the predicted agonistic effect of the metabolite descyano-thiacloprid (DCNT).