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A synergized machine learning plus cross-species wet-lab validation approach identifies neuronal mitophagy inducers inhibiting Alzheimer disease
Ai, Ruixue1; Zhuang, Xu Xu2; Anisimov, Alexander1; Lu, Jia Hong2; Fang, Evandro F.1,3
2022
Source PublicationAutophagy
ISSN1554-8627
Volume18Issue:4Pages:939-941
Abstract

Failed recognition and clearance of damaged mitochondria contributes to memory loss as well as Aβ and MAPT/Tau pathologies in Alzheimer disease (AD), for which there is an unmet therapeutic need. Restoring mitophagy to eliminate damaged mitochondria could abrogate metabolic dysfunction, neurodegeneration and may subsequently inhibit or slow down cognitive decline in AD models. We have developed a high-throughput machine-learning approach combined with a cross-species screening platform to discover novel mitophagy-inducing compounds from a natural product library and further experimentally validated the potential candidates. Two lead compounds, kaempferol and rhapontigenin, induce neuronal mitophagy and reduce Aβ and MAPT/Tau pathologies in a PINK1-dependent manner in both C. elegans and mouse models of AD. Our combinational approach provides a fast, cost-effective, and highly accurate method for identification of potent mitophagy inducers to maintain brain health.

KeywordAging Alzheimer’s Disease Autophagy Machine Learning Mitophagy
DOI10.1080/15548627.2022.2031382
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaCell Biology
WOS SubjectCell Biology
WOS IDWOS:000752356900001
Scopus ID2-s2.0-85124910103
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Citation statistics
Document TypeJournal article
CollectionInstitute of Chinese Medical Sciences
Corresponding AuthorLu, Jia Hong; Fang, Evandro F.
Affiliation1.Department of Clinical Molecular Biology, University of Oslo and Akershus University Hospital, Lørenskog, Norway
2.State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao
3.The Norwegian Centre on Healthy Ageing (NO-Age), Oslo, Norway
Corresponding Author AffilicationInstitute of Chinese Medical Sciences
Recommended Citation
GB/T 7714
Ai, Ruixue,Zhuang, Xu Xu,Anisimov, Alexander,et al. A synergized machine learning plus cross-species wet-lab validation approach identifies neuronal mitophagy inducers inhibiting Alzheimer disease[J]. Autophagy, 2022, 18(4), 939-941.
APA Ai, Ruixue., Zhuang, Xu Xu., Anisimov, Alexander., Lu, Jia Hong., & Fang, Evandro F. (2022). A synergized machine learning plus cross-species wet-lab validation approach identifies neuronal mitophagy inducers inhibiting Alzheimer disease. Autophagy, 18(4), 939-941.
MLA Ai, Ruixue,et al."A synergized machine learning plus cross-species wet-lab validation approach identifies neuronal mitophagy inducers inhibiting Alzheimer disease".Autophagy 18.4(2022):939-941.
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