Tail regeneration and other phenomena of wound healing and tissue restoration in lizards
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Wound healing is a fundamental evolutionary adaptation with two possible outcomes: scar formation or reparative regeneration. Scars participate in re-forming the barrier with the external environment and restoring homeostasis to injured tissues, but are well understood to represent dysfunctional replacements. In contrast, reparative regeneration is a tissue-specific program that near-perfectly replicates that which was lost or damaged. Although regeneration is best known from salamanders (including newts and axolotls) and zebrafish, it is unexpectedly widespread among vertebrates. For example, mice and humans can replace their digit tips, while many lizards can spontaneously regenerate almost their entire tail. Whereas the phenomenon of lizard tail regeneration has long been recognized, many details of this process remain poorly understood. All of this is beginning to change. This Review provides a comparative perspective on mechanisms of wound healing and regeneration, with a focus on lizards as an emerging model. Not only are lizards able to regrow cartilage and the spinal cord following tail loss, some species can also regenerate tissues after full-thickness skin wounds to the body, transections of the optic nerve and even lesions to parts of the brain. Current investigations are advancing our understanding of the biological requirements for successful tissue and organ repair, with obvious implications for biomedical sciences and regenerative medicine.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it