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<p>Mitophagy, the selective autophagic elimination of mitochondria, is essential for maintaining mitochondrial quality and cell homeostasis. Impairment of mitophagy flux, a process involving multiple sequential intermediates, is implicated in the onset of numerous neurodegenerative diseases. Screening mitophagy inducers, particularly understanding their impact on mitophagic intermediates, is crucial for neurodegenerative disease treatment. However, existing techniques do not allow simultaneous visualization of distinct mitophagic intermediates in live cells. Here, we introduce an artificial intelligence-assisted fluorescence microscopic system (AI-FM) that enables the uninterrupted recognition and quantification of key mitophagic intermediates by extracting mitochondrial pH and morphological features. Using AI-FM, we identify a potential mitophagy modulator, Y040-7904, which enhances mitophagy by promoting mitochondria transport to autophagosomes and the fusion of autophagosomes with autolysosomes. Y040-7904 also reduces amyloid-β pathologies in&#xa0;both in vitro and in vivo models of Alzheimer’s disease. This work offers an approach for visualizing the entire mitophagy flux, advancing the understanding of mitophagy-related mechanisms and enabling the discovery of mitophagy inducers for neurodegenerative diseases.</p>

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An AI-assisted fluorescence microscopic system for screening mitophagy inducers by simultaneous analysis of mitophagic intermediates

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月4日

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  • Yicheng Wang,
  • Pengfei Song,
  • Heqing Zhou,
  • Pengwei Wang,
  • Yan Li,
  • Zhiyong Shao,
  • Lu Wang,
  • Yan You,
  • Zuhai Lei,
  • Jinhua Yu,
  • Cong Li

摘要

Mitophagy, the selective autophagic elimination of mitochondria, is essential for maintaining mitochondrial quality and cell homeostasis. Impairment of mitophagy flux, a process involving multiple sequential intermediates, is implicated in the onset of numerous neurodegenerative diseases. Screening mitophagy inducers, particularly understanding their impact on mitophagic intermediates, is crucial for neurodegenerative disease treatment. However, existing techniques do not allow simultaneous visualization of distinct mitophagic intermediates in live cells. Here, we introduce an artificial intelligence-assisted fluorescence microscopic system (AI-FM) that enables the uninterrupted recognition and quantification of key mitophagic intermediates by extracting mitochondrial pH and morphological features. Using AI-FM, we identify a potential mitophagy modulator, Y040-7904, which enhances mitophagy by promoting mitochondria transport to autophagosomes and the fusion of autophagosomes with autolysosomes. Y040-7904 also reduces amyloid-β pathologies in both in vitro and in vivo models of Alzheimer’s disease. This work offers an approach for visualizing the entire mitophagy flux, advancing the understanding of mitophagy-related mechanisms and enabling the discovery of mitophagy inducers for neurodegenerative diseases.