Epithelial to mesenchymal transition is mediated by both TGF-β canonical and non-canonical signaling during axolotl limb regeneration
Bibliographic record
Abstract
Axolotls have the amazing ability to regenerate. When compared to humans, axolotls display a very fast wound closure, no scarring and are capable to replace lost appendages perfectly. Understanding the signaling mechanism leading to this perfect healing is a key step to help develop regenerative treatments for humans. In this paper, we studied cellular pathways leading to axolotl limb regeneration. We focus on the wound closure phase where keratinocytes migrate to close the lesion site and how epithelial to mesenchymal transitions are involved in this process. We observe a correlation between wound closure and EMT marker expression. Functional analyses using pharmacological inhibitors showed that the TGF-β/SMAD (canonical) and the TGF-β/p38/JNK (non-canonical) pathways play a role in the rate to which the keratinocytes can migrate. When we treat the animals with a combination of inhibitors blocking both canonical and non-canonical TGF-β pathways, it greatly reduced the rate of wound closure and had significant effects on certain known EMT genes.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".