ReviewCell biology and toxicology2026
The application progress of organoid technology in the toxicity assessment of environmental pollutants.
Review in Cell biology and toxicology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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9 authors.
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Abstract
Human production activities and daily life are the main sources of environmental pollutants, and their potential health impacts have attracted growing attention. Currently, the assessment of environmental pollutant toxicity depends heavily on animal models and some cell culture models. However, these approaches have inherent limitations, such as their inability to recapitulate the in vivo microenvironment and the presence of interspecies differences. Organoids not only recapitulate cell types and tissue structures of human organs, but also exhibit key physiological functions, rendering them ideal alternative models for assessing the health risks of environmental pollutants. In this review, we briefly introduce the development history of organoids as models for environmental pollutant toxicity assessment. Additionally, organoids are categorized by cell sources, and current mainstream organoid culture techniques are systematically summarized. Next, we highlight the application value of typical organoids including lung, brain, cardiac, intestine, liver and kidney organoids in environmental pollutant toxicity assessment. Finally, we thoroughly analyze the strengths and limitations of organoid models for such toxicity testing. Therefore, this review aims to advance organoid technology, and provide new insights into the toxicity assessment of environmental pollutants and the exploration of relevant toxic mechanisms.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.