<i>Tgf‐β</i> superfamily and limb regeneration: <i>Tgf‐β</i> to start and <i>Bmp</i> to end
Bibliographic record
Abstract
Axolotls represent a popular model to study how nature solved the problem of regenerating lost appendages in tetrapods. Our work over many years focused on trying to understand how these animals can achieve such a feat and not end up with a scarred up stump. The Tgf-β superfamily represents an interesting family to target since they are involved in wound healing in adults and pattern formation during development. This family is large and comprises Tgf-β, Bmps, activins and GDFs. In this review, we present work from us and others on Tgf-β & Bmps and highlight interesting observations between these two sub-families. Tgf-β is important for the preparation phase of regeneration and Bmps for the redevelopment phase and they do not overlap with one another. We present novel data showing that the Tgf-β non-canonical pathway is also not active during redevelopment. Finally, we propose a molecular model to explain how Tgf-β and Bmps maintain distinct windows of expression during regeneration in axolotls.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".