Skin wound healing in axolotls: a scarless process
Bibliographic record
Abstract
Urodele amphibians, such as the axolotl (Ambystoma mexicanum), have the unique faculty among vertebrates to regenerate lost appendages (limbs and tail) and other body parts (apex of the heart, forebrain and jaw) after amputation. Interestingly, axolotls never seem to form scar tissue at the site of amputation once regeneration is completed. Before now, very few studies were directly focused on the description of the events happening during wound healing after a skin injury in salamanders. In this paper, we directly investigated skin wound healing after excisional wounding which removed the epidermis, dermis and basement membrane in the axolotl. Axolotls were wounded with a 1.5-mm skin biopsy punch. Results show rapid re-epithelialization of the wound within 8 hrs after wounding. Histological analysis of wound healing confirmed the absence of tissue fibrosis throughout the process and shows that skin integrity is re-established by 90 days after wounding. Results also reveal the absence of neutrophils in the wound area, suggestive of a lack of or low inflammatory response. The expression of proteins central to wound healing seemed different than in mammals as α-smooth muscle actin was absent and transforming growth factor β-1 was only transiently expressed during wound healing in the axolotl. Finally, subcutaneous injections of bleomycin were performed to verify whether the induction of scar tissue was possible in axolotls. Surprisingly, results show that axolotls are not resistant to bleomycin-induced tissue fibrosis, but the resulting scar tissue does not seem to contain significant amounts of collagen.
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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) | 0.001 | 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".