Microcystin LR (MC LR) and cylindrospermopsin (CYN) are cyanobacterial toxins commonly detected during harmful algal blooms in freshwater systems. Their increasing occurrence raises concerns about water quality and potential risks to human health. Although the liver is their target organ, these cyanotoxins can also affect the nervous system. The potential neurotoxicity of MC-LR and CYN is still scarcely investigated, particularly for CYN. In this study, the effects of both cyanotoxins on neural progenitor cells were evaluated. MC-LR did not significantly affect cell viability at concentrations up to 60 µM, whereas CYN induced evident cytotoxicity starting at 1 µM after 24-48 h. Additionally, CYN was also tested in BrainSpheres (also called brain microphysiological system, bMPS) for the first time. Statistically significant cytotoxicity was observed from 1 µM onward after 1 week exposure. Downstream analysis revealed that subcytotoxic concentrations of CYN altered the gene expression of different nervous (TUBB3, NEFH, SYP, OLIG1, and GFAP), inflammatory (IL-1β, TNF-α and Nf-κβ) and oxidative stress (SOD1, HMOX and GSTT) markers analysed by RT-qPCR. Overall, the results obtained showed that BrainSpheres is an effective new approach methodology for evaluating the neurotoxic potential of cyanotoxins and points out the importance of including neurotoxicity in the risk assessment of cyanotoxins to human health.

Microplastics (MPs) and nanoplastics (NPs) represent an emerging issue for human and animal health. This review critically examines in vitro and in vivo studies to elucidate their mechanisms of action and toxicological effects. Key objectives included: providing a comprehensive overview of MP-NPs studies in literature, assessing experimental conditions relative to real environmental scenarios, and identifying toxicological pathways at the molecular level. The findings revealed significant progress in understanding MP-NPs impacts. In particular, it has been observed the promotion of inflammation, oxidative stress, apoptosis, autophagy, and endoplasmic reticulum (ER) stress via specific signaling axes. Reproductive toxicity emerged as the primary research focus, particularly in male models, whereas effects on gastrointestinal, neurological, and cardiovascular systems were insufficiently studied, especially for the molecular pathways affected. Most studies disproportionately focused on polystyrene particles, neglecting other prevalent polymers such as polyethylene and polypropylene. Furthermore, reliance on synthetic microspheres and non-realistic experimental concentrations limits relevance to real-world conditions. Limited long-term exposure studies further constrain the understanding of MP-NPs persistence and risks. In view of this, future research should integrate environmentally relevant conditions for particles doses, size and composition, long-term exposure assessments, and advanced methodologies such as omics and computational modeling. In addition, therapeutic interventions targeting oxidative and ER stress, inflammation and apoptosis may be an excellent solution to mitigate MP-NPs toxicity. At the same time, a standardized global approach is needed to fully understand the risks posed by MP-NPs, attempting to safeguard public and environmental health.

Propylene glycol ethers (PGEs) are mixtures of an α-isomer and a β-isomer (β-PGE) that is oxidized via alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH) to potentially neurotoxic alkoxy propionic acids (β-metabolites). While the liver is the primary organ for ADH- and ALDH-mediated metabolism, the contribution to the metabolism of β-PGEs by the blood-brain barrier (BBB) and the brain remains unknown. Here, we aimed to assess the neurotoxic potential of PGEs after systemic exposure by (1) comparing 3D HepaRG and human liver subcellular fraction (S9) for the in vitro determination of the kinetics of hepatic metabolism for β-PGEs, (2) evaluating the BBB-permeability of PGEs and β-metabolites, (3) determining the presence of ADH1 and ALDH2 and the extent of metabolization of β-PGEs in the BBB and brain. The results show that 3D HepaRG and S9 served as competent systems to estimate the enzymatic kinetic (clearance) for β-metabolite formation. We observed that PGEs and the β-metabolites could cross the BBB, based on their permeance across a cellular barrier consisting of the hCMEC/D3 cell line. Metabolic enzymes were not exclusive to the liver, as expression of ADH1 and ALDH2 was demonstrated using RT-qPCR, Western blot, and immunostainings in the BBB in vitro models and in BrainSpheres. Furthermore, LC-MS/MS quantification of the β-metabolites in all in vitro models revealed that 3D HepaRG had a similar metabolic capacity to primary human hepatocytes and that the amount of β-metabolite formed per protein in the BBB was approximately 10-30 % of that in the liver. We also demonstrated active metabolism in the BrainSpheres. In conclusion, the hepatic in vitro models provided data that will help to refine toxicokinetic models and predict internal exposures, thereby supporting the risk assessment of PGEs. In addition, the high permeance of the PGEs and the β-metabolites across the BBB increases the plausibility of neurotoxicity upon systemic exposure. This is further supported by the presence of active ADH1 and ALDH2 enzymes in the BBB in vitro systems and in BrainSpheres, suggesting metabolite formation in the central nervous system. Hence, we suggest that BBB-permeance and extra-hepatic metabolism of the β-PGEs may contribute to the neurotoxicity of PGEs.

The global rise of environmental contaminants (ECs), including microplastics, heavy metals, pesticides, and drugs, poses an urgent threat to human health. Traditional toxicological models often fail to replicate human-specific responses, delaying effective risk assessment and regulation. Conversely, human organoid models represent a breakthrough in environmental health research by offering unprecedented physiological relevance. Hence, this review highlights the potential role of human organoids in ECs toxicity assessment. Results showed that current studies primarily focus on drugs, while perfluorinated compounds, solvents and dietary toxicants remain understudied. A major shortcoming is the overreliance on acute, high-dose exposure models that fail to mimic real-world situations. Thus, incorporating chronic, low-dose exposures is essential for ecological and regulatory relevance. Regarding the model, induced pluripotent stem cell derived organoids are the most used, while adult stem cell- and patient-derived models remain underutilized despite their potential for clinical research. Also, standardization challenges, especially variability in organoid architecture, cellular diversity, and reproducibility, continue to limit their broad application. Mechanistic insights reveal that ECs disrupt key signaling pathways (Wnt/β-catenin, MAPK, Notch, BMP, p53) inducing altered cell differentiation, inflammation, structural changes and apoptosis. As regards the assays, reliance on the conventional ones restricts molecular depth. Indeed, advanced multi-omics and AI-driven analyses remain underexploited, despite their promise for environmental toxicology. To accelerate progress, future efforts must integrate low and chronic exposure with multi-organoid platforms and AI-based profiling to better capture systemic and tissue specific responses to ECs. Doing so will revolutionize hazard assessment and support more effective environmental health policies worldwide.

Unraveling the associations between human exposure to environmental chemicals and potential neurotoxicity presents significant challenges. Evaluation of neurotoxicity potential using animal testing is resource-intensive (financial, labor, and animal use) and faces uncertainties regarding biological relevance to human health outcomes. Therefore, there is a need to develop efficient and human-relevant in vitro new approach methodologies (NAMs) to screen and evaluate chemicals for neurotoxicity potential. Recording of neural network activity using microelectrode array (MEA) technology has been identified as a reliable and reproducible method for evaluating neurotoxicity. Much of this research has been performed in 2D rodent-derived cell models. The 'BrainSpheres MEA assay' described in this study offers a promising functional human induced pluripotent stem cell (iPSC)-derived 3D brain model comprising neurons, astrocytes, and oligodendrocytes. We demonstrate consistent spontaneous neuronal firing and network bursting parameters from 7-week-old BrainSpheres using a high-density MEA technology. The performance of this model as a human-relevant NAM was evaluated by conducting a multi-concentration, 13 day exposure study with a set of ten chemicals. Neural activity metrics were assessed and compared to results from a 2D-MEA assay using rodent cells. Loperamide and domoic acid (two assay positive controls) demonstrated similar bioactivity profiles in the BrainSphere MEA assay to the 2D-MEA assay, while acetaminophen (assay negative control) was inactive in both assays. The 2D-MEA model demonstrated more potent bioactivity for 4/7 chemicals that were active in both assays. In the future, reducing replicate variability and testing a larger set of chemicals will likely improve the accuracy and reliability of the assay. These preliminary findings suggest that the BrainSphere assay could be used alongside the rat network formation assay (rNFA) as part of a tiered strategy, where hits in the rNFA are confirmed and further characterized in the BrainSphere model, helping move toward animal-free toxicological testing.

Exposure to solvents may contribute to the development of neurodevelopmental and neurodegenerative diseases. Glycol ethers consist in a widely used class of organic solvents leading to workers and consumers exposure via many applications. Ethylene glycol ethers are gradually being replaced by propylene glycol ethers thought to be less toxic. However, their neurotoxicity is not systematically assessed before placing them on the market. Therefore, this study investigated the potential neurotoxicity of propylene glycol butyl ether (PGBE) for which no official occupational limit has been established. To this aim, new approach methodologies have been used. Human induced pluripotent stem cells-derived BrainSpheres model was exposed to PGBE and to its assumed human main metabolite, 2-butoxypropanoic acid (2BPA). An integrative multiomic approach (transcriptomics, proteomics, metabolomics and lipidomics) was adopted to assess molecular alterations, derive benchmark concentrations and define potential mechanisms of action. PGBE was neurotoxic at occupationally relevant exposure concentrations. This was shown for the first time in human cells. Although PGBE was more cytotoxic than 2BPA, both compounds showed very similar neurotoxicity. PGBE and 2BPA strongly affected the cell cycle, induced oxidative stress and perturbed energy and lipid metabolism. They also targeted specific nervous system processes, such as axon guidance and synapse organization. Finally, 2BPA might trigger ferroptosis by increased iron uptake. Our in vitro results show an urgent need for public health authorities to carefully assess the risk glycol ethers pose to humans, to properly protect the workers as well as individuals in the general population unknowingly exposed from indoor air contaminations.

Cell culture technology has evolved, moving from single-cell and monolayer methods to 3D models like reaggregates, spheroids, and organoids, improved with bioengineering like microfabrication and bioprinting. These advancements, termed microphysiological systems (MPSs), closely replicate tissue environments and human physiology, enhancing research and biomedical uses. However, MPS complexity introduces standardization challenges, impacting reproducibility and trust. We offer guidelines for quality management and control criteria specific to MPSs, facilitating reliable outcomes without stifling innovation. Our fit-for-purpose recommendations provide actionable advice for achieving consistent MPS performance.

Detailed method descriptions are essential for reproducibility, research evaluation, and effective data reuse. We summarize the key recommendations for life sciences researchers and research institutions described in the European Commission PRO-MaP report.

BackgroundChemicals are not required to be tested systematically for their neurotoxic potency, although they may contribute to the development of several neurological diseases. The absence of systematic testing may be partially explained by the current Organisation for Economic Co-operation and Development (OECD) Test Guidelines, which rely on animal experiments that are expensive, laborious, and ethically debatable. Therefore, it is important to understand the risks to exposed workers and the general population exposed to domestic products. In this study, we propose a strategy to test the neurotoxicity of solvents using the commonly used glycol ethers as a case study. ObjectiveThis study aims to provide a strategy that can be used by regulatory agencies and industries to rank solvents according to their neurotoxicity and demonstrate the use of toxicokinetic modeling to predict air concentrations of solvents that are below the no observed adverse effect concentrations (NOAECs) for human neurotoxicity determined in in vitro assays. MethodsThe proposed strategy focuses on a complex 3D in vitro brain model (BrainSpheres) derived from human-induced pluripotent stem cells (hiPSCs). This model is accompanied by in vivo, in vitro, and in silico models for the blood-brain barrier (BBB) and in vitro models for liver metabolism. The data are integrated into a toxicokinetic model. Internal concentrations predicted using this toxicokinetic model are compared with the results from in vivo human-controlled exposure experiments for model validation. The toxicokinetic model is then used in reverse dosimetry to predict air concentrations, leading to brain concentrations lower than the NOAECs determined in the hiPSC-derived 3D brain model. These predictions will contribute to the protection of exposed workers and the general population with domestic exposures. ResultsThe Swiss Centre for Applied Human Toxicology funded the project, commencing in January 2021. The Human Ethics Committee approval was obtained on November 16, 2022. Zebrafish experiments and in vitro methods started in February 2021, whereas recruitment of human volunteers started in 2022 after the COVID-19 pandemic–related restrictions were lifted. We anticipate that we will be able to provide a neurotoxicity testing strategy by 2026 and predicted air concentrations for 6 commonly used propylene glycol ethers based on toxicokinetic models incorporating liver metabolism, BBB leakage parameters, and brain toxicity. ConclusionsThis study will be of great interest to regulatory agencies and chemical industries needing and seeking novel solutions to develop human chemical risk assessments. It will contribute to protecting human health from the deleterious effects of environmental chemicals. International Registered Report Identifier (IRRID)DERR1-10.2196/50300

With a recent amendment, India joined other countries that have removed the legislative barrier toward the use of human-relevant methods in drug development. Here, global stakeholders weigh in on the urgent need to globally harmonize the guidelines toward the standardization of microphysiological systems. We discuss a possible framework for establishing scientific confidence and regulatory approval of these methods.

For ethical, economical, and scientific reasons, animal experimentation, used to evaluate the potential neurotoxicity of chemicals before their release in the market, needs to be replaced by new approach methodologies. To illustrate the use of new approach methodologies, the human induced pluripotent stem cell-derived 3D model BrainSpheres was acutely (48 h) or repeatedly (7 days) exposed to amiodarone (0.625–15 µM), a lipophilic antiarrhythmic drug reported to have deleterious effects on the nervous system. Neurotoxicity was assessed using transcriptomics, the immunohistochemistry of cell type-specific markers, and real-time reverse transcription–polymerase chain reaction for various genes involved in the lipid metabolism. By integrating distribution kinetics modeling with neurotoxicity readouts, we show that the observed time- and concentration-dependent increase in the neurotoxic effects of amiodarone is driven by the cellular accumulation of amiodarone after repeated dosing. The development of a compartmental in vitro distribution kinetics model allowed us to predict the change in cell-associated concentrations in BrainSpheres with time and for different exposure scenarios. The results suggest that human cells are intrinsically more sensitive to amiodarone than rodent cells. Amiodarone-induced regulation of lipid metabolism genes was observed in brain cells for the first time. Astrocytes appeared to be the most sensitive human brain cell type in vitro. In conclusion, assessing readouts at different molecular levels after the repeat dosing of human induced pluripotent stem cell-derived BrainSpheres in combination with the compartmental modeling of in vitro kinetics provides a mechanistic means to assess neurotoxicity pathways and refine chemical safety assessment for humans.

Nanomaterials have been extensively studied in cancer therapy as vectors that may improve drug delivery.Such vectors not only bring numerous advantages such as stability, biocompatibility, and cellular uptake but have also been shown to overcome some cancer-related resistances.Nanocarrier can deliver the drug more precisely to the specific organ while improving its pharmacokinetics, thereby avoiding secondary adverse effects on the not target tissue.Between these nanovectors, diverse material types can be discerned, such as liposomes, dendrimers, carbon nanostructures, nanoparticles, nanowires, etc., each of which offers different opportunities for cancer therapy.In this review, a broad spectrum of nanovectors is analyzed for application in multimodal cancer therapy and diagnostics in terms of mode of action and pharmacokinetics.Advantages and inconveniences of promising nanovectors, including gold nanostructures, SPIONs, semiconducting quantum dots, various nanostructures, phospholipid-based liposomes, dendrimers, polymeric micelles, extracellular and exome vesicles are summarized.The article is concluded with a future outlook on this promising field.

Despite its suitability to analyze polar metabolites using minute amounts of sample and its large peak capacity, CE-MS has traditionally been considered to lack the robustness required by untargeted metabolomics, especially in regulatory environments. This belief comes from the difficulty to adequately identify metabolites based on their migration times due to the variability of such parameter. In the present work, we demonstrate how this limitation can be circumvented by using standardized CE-MS conditions and automatically converting CE-MS files into electrophoretic mobility (& mu;eff) scale. This strategy allows to conveniently exploit the advantages of CE-MS for low-volume samples generated during the toxicological risk assessment of potential neuroinflammatory substances, performed via the evaluation of astrocyte reaction. Human astrocyte cells were exposed to tumor necrosis factor alpha (TNF & alpha;) as a model compound and to digoxin at different concentrations as a tested chemical. The induced metabolic profiles were then characterized by means of CE-MS metabolomics and the success of the annotation step was evaluated and compared when one or two reference compounds were used as markers for the conversion into the effective electrophoretic mobility scale. The use of two markers resulted in a more reliable metabolite identification across all the conditions. As a result, a total of 68 anionic and cationic metabolites were annotated in both CE polarities. Unsupervised and supervised multivariate analysis enabled the comparison of the metabolomic profiles induced by each compound, highlighting common and differential metabolites, suggesting a similar but specific mechanism of activation for digoxin with regard to TNF & alpha;. CE-MSbased metabolomics is an advantageous tool for the analysis of minute amounts of samples delivered by new approach methodologies (NAMs) in chemical risk assessment, allowing high throughput toxicity screening.

To transfer toxicological findings from model systems, e.g. animals, to humans, standardized safety factors are applied to account for intra-species and inter-species variabilities. An alternative approach would be to measure and model the actual compound-specific uncertainties. This biological concept assumes that all observed toxicities depend not only on the exposure situation (environment = E), but also on the genetic (G) background of the model (G × E). As a quantitative discipline, toxicology needs to move beyond merely qualitative G × E concepts. Research programs are required that determine the major biological variabilities affecting toxicity and categorize their relative weights and contributions. In a complementary approach, detailed case studies need to explore the role of genetic backgrounds in the adverse effects of defined chemicals. In addition, current understanding of the selection and propagation of adverse outcome pathways (AOP) in different biological environments is very limited. To improve understanding, a particular focus is required on modulatory and counter-regulatory steps. For quantitative approaches to address uncertainties, the concept of “genetic” influence needs a more precise definition. What is usually meant by this term in the context of G × E are the protein functions encoded by the genes. Besides the gene sequence, the regulation of the gene expression and function should also be accounted for. The widened concept of past and present “gene expression” influences is summarized here as Ge. Also, the concept of “environment” needs some re-consideration in situations where exposure timing (Et) is pivotal: prolonged or repeated exposure to the insult (chemical, physical, life style) affects Ge. This implies that it changes the model system. The interaction of Ge with Et might be denoted as Ge × Et. We provide here general explanations and specific examples for this concept and show how it could be applied in the context of New Approach Methodologies (NAM).