Scar‐Free Wound Healing and Regeneration Following Tail Loss in the Leopard Gecko, <i>Eublepharis macularius</i>
Bibliographic record
Abstract
Many lizards are able to undergo scar-free wound healing and regeneration following loss of the tail. In most instances, lizard tail loss is facilitated by autotomy, an evolved mechanism that permits the tail to be self-detached at pre-existing fracture planes. However, it has also been reported that the tail can regenerate following surgical amputation outside the fracture plane. In this study, we used the leopard gecko, Eublepharis macularius, to investigate and compare wound healing and regeneration following autotomy at a fracture plane and amputation outside the fracture plane. Both forms of tail loss undergo a nearly identical sequence of events leading to scar-free wound healing and regeneration. Early wound healing is characterized by transient myofibroblasts and the formation of a highly proliferative wound epithelium immunoreactive for the wound keratin marker WE6. The new tail forms from what is commonly referred to as a blastema, a mass of proliferating mesenchymal-like cells. Blastema cells express the protease matrix metalloproteinase-9. Apoptosis (demonstrated by activated caspase 3 immunostaining) is largely restricted to isolated cells of the original and regenerating tail tissues, although cell death also occurs within dermal structures at the original-regenerated tissue interface and among clusters of newly formed myocytes. Furthermore, the autotomized tail is unique in demonstrating apoptosis among cells adjacent to the fracture planes. Unlike mammals, transforming growth factor-β3 is not involved in wound healing. We demonstrate that scar-free wound healing and regeneration are intrinsic properties of the tail, unrelated to the location or mode of tail detachment.
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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".