mTOR inhibits autophagy to facilitate cell swelling and rapid wound repair
Bibliographic record
Abstract
SUMMARY Embryonic wounds repair rapidly, with no inflammation or scarring. Embryonic wound healing is driven by collective cell movements facilitated by the swelling of the cells adjacent to the wound. The mechanistic target of rapamycin complex 1 (mTORC1) is often associated with cell growth. We found that disrupting mTORC1 signalling prevented cell swelling and slowed down wound repair. Catabolic processes, such as autophagy, can inhibit cell growth. Using five-dimensional time-lapse microscopy, as well as pharmacological and genetic manipulations, we demonstrated that the number of autophagosomes decreased during wound repair, suggesting that autophagy must be tightly regulated for rapid wound healing. Quantitative image analysis showed that mTOR inhibition increased autophagy, and that activating autophagy prevented cell swelling and slowed down embryonic wound closure. Finally, reducing autophagy in embryos in which mTORC1 signalling was disrupted rescued rapid wound repair. Together, our results show that mTORC1 activation upon wounding negatively regulates autophagy, allowing cells to increase their volumes to facilitate rapid wound healing.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".