Real-Time Monitoring of Adenosine Triphosphate Fluctuation in Lysosome during Autophagy/Mitophagy
Bibliographic record
Abstract
Abstract Autophagy, a lysosomal degradation pathway critical for cell survival, differentiation, development, and maintaining homeostasis, plays a crucial role in cellular health. Maintaining an adequate level of adenosine triphosphate (ATP), the central molecule in energy metabolism, is equally essential for these processes. However, the interplay between autophagy and energy metabolism remains incompletely understood due to technical challenges, including the need for high-precision, dynamic detection within organelles, and sensitivity to the acidic lysosomal environment. To address these limitations, we developed HR-MP, a ratiometric fluorogenic nanoprobe specifically designed for visualizing ATP levels in acidic lysosomes during autophagy. HR-MP exhibits selective, rapid, and quantitative ATP detection in vitro, allowing it to quantitatively monitor lysosomal ATP fluctuations in complex biological environments with excellent biocompatibility, membrane permeability, and lysosome-targeting ability. Importantly, HR-MP enables real-time tracking of ATP fluctuations during starvation- or drug-induced autophagy in living cells, providing a powerful tool for elucidating the links between autophagy and energy metabolism.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".