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Yeast Chronological Lifespan Model as a Tool for Screening Aging Interventions
Pingkang Xu, Xinyu Zhang, Yuanxia Wang, Sajid Ur Rahman, Dejian Huang, Ziyun Wu
International Journal of Molecular Sciences · 2026 · ▲ 1 citations
Abstract
is a useful model to understand the biochemistry and biology of aging. Yeast speeds up the aging study due to its short lifespan, well-established genetics, and simple measurement for lifespan. The chronological lifespan in yeast specifically emphasizes the survival rate of the population, providing data that offer more direct feedback on experimental treatments than replicative lifespan. The advancement of the yeast chronological lifespan assay has enabled researchers to efficiently screen numerous potential antiaging compounds and delve into aging theories. Through the integration of robust genetic screening and high-throughput technologies, the yeast model has facilitated the identification of various antiaging factors with potential applications in humans, shedding light on the genetic mechanisms of aging. Many natural products, similar to calorie restriction, have been shown to effectively extend the lifespan of yeast, a benefit that is also conserved in mammals. In this review, we highlight the nutrient factors, natural compounds, and genes that contribute to extending the yeast lifespan, as well as the genetic regulations underlying the aging process in yeast.
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- OpenAlex
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- 10.3390/ijms27062633
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- 2026-07-15 MST
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APA
Xu, P., Zhang, X., Wang, Y., Rahman, S.U., Huang, D., & Wu, Z. (2026). Yeast Chronological Lifespan Model as a Tool for Screening Aging Interventions. <em>International Journal of Molecular Sciences</em>. https://doi.org/10.3390/ijms27062633
Vancouver
Xu P, Zhang X, Wang Y, Rahman SU, Huang D, Wu Z. Yeast Chronological Lifespan Model as a Tool for Screening Aging Interventions. International Journal of Molecular Sciences. 2026. doi:10.3390/ijms27062633.
BibTeX
@article{pingkang2026YeastC,
title = {Yeast Chronological Lifespan Model as a Tool for Screening Aging Interventions},
author = {Pingkang Xu and Xinyu Zhang and Yuanxia Wang and Sajid Ur Rahman and Dejian Huang and Ziyun Wu},
journal = {International Journal of Molecular Sciences},
year = {2026},
doi = {10.3390/ijms27062633},
}
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