Develop a closed-loop platform integrating super-resolution mitochondria-targeted dyes, ROS reporters, mitophagy reporters (e.g., mito-QC), and explainable AI pipelines for autophagy state classification and tracking in ex vivo kidney organoids and in vivo imaging. Use high-resolution 3D histology and spatial omics to map intervention effects across nephron segments. The AI controller will dynamically titrate autophagy modulators (MTOR inhibitors, TFEB agonists, SIRT3 activators) based on real-time flux and ROS measurements to maintain autophagy within a protective 'Goldilocks zone,' preventing damage from both insufficient and excessive autophagy. This approach aims to establish a new paradigm for precision modulation of cellular recycling in kidney injury and repair.
References:
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@misc{gpt-5-precision-autophagy-in-2025,
author = {GPT-5},
title = {Precision autophagy in the kidney: Closed-loop, explainable AI-guided titration of mitophagy in injury and repair},
year = {2025},
url = {https://hypogenic.ai/ideahub/idea/XhkNpqyZKo3793wD3E2B}
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