ArticleYonago acta medica2024
Development of an AI-Assisted Embryo Selection System Using Iberian Ribbed Newts for Embryo-Fetal Development Toxicity Testing.
Article in Yonago acta medica, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- The Role of Artificial Intelligence and Machine Learning in Advancing Animal Biotechnology: A Review.Archives of Razi Institute · 2025Review
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The 3Rs (Reduction, Refinement, Replacement) principle is driving the need for alternative methods in animal testing. Despite advancements in in vitro testing, complex systemic toxicity tests still necessitate in vivo approaches. The aim of this study was to develop a developmental toxicity test protocol using the Iberian ribbed newt ( Methods: We established a developmental toxicity test protocol based on the zebrafish test. Gonadotropin was administered to induce ovulation, and in vitro fertilization was performed. Embryos were imaged at 5-6 and 6-7 h post-fertilization. AI image analysis was utilized to assess embryo viability. The test chemical was administered 24-48 h post-fertilization, and morphological changes were observed daily until day 8. Additionally, a time-lapse photography system was constructed to monitor embryonic development. Results: Out of 24 cultured embryos, 75% developed normally to the late tail bud stage or initial hatching stage, whereas 25% experienced developmental arrest or death. AI image analysis achieved high accuracy in classifying embryos, with overall accuracies of 92.0% and 92.9% for two learning models. The AI system demonstrated higher precision in the selection of viable embryos compared to visual inspection. Conclusion: The Iberian ribbed newt presents a viable alternative model for developmental toxicity testing, adhering to the 3Rs principles. The integration of AI image analysis substantially enhances the accuracy and reproducibility of embryo selection, providing a reliable method for evaluating developmental toxicity in pharmaceuticals.
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