p21 <sup>−/−</sup> Mice Exhibit Spontaneous Articular Cartilage Regeneration Post-Injury
Bibliographic record
Abstract
Objective Recent studies have implicated the cyclin dependent kinase inhibitor, p21, in enhanced tissue regeneration observed in MRL/MpJ “super-healer” mice. Specifically, p21 is downregulated in MRL cells and similar ear hole closure to MRL mice has been observed in p21 −/− mice. However, the direct implications of p21 deletion in endogenous articular cartilage regeneration remain unknown. In this study, we investigated the role of p21 deletion in the ability of mice to heal full-thickness cartilage defects (FTCDs). Design C57BL/6 and p21 −/− ( Cdkn1a tm1Tyj ) mice were subjected to FTCD and assessment of cartilage healing was performed at 1 hour, 3 days, 1 week, 2 weeks, and 4 weeks post-FTCD using a 14-point histological scoring system. X-ray microscopy was used to quantify cartilage healing parameters (e.g., cartilage thickness, surface area/volume) between C57BL/6 and p21 −/− mice. Results Absence of p21 resulted in increased spontaneous articular cartilage regeneration by 3 days post-FTCD. Furthermore, p21 −/− mice presented with increased cartilage thickness at 1 and 2 weeks post-FTCD compared with uninjured controls, returning to baseline by 4 weeks post-FTCD. Conclusions We report that p21 −/− mice display enhanced articular cartilage regeneration post-FTCD compared with C57BL/6 mice. Furthermore, cartilage thickness was increased in p21 −/− mice at 1 week post-FTCD compared with uninjured p21 −/− mice and C57BL/6 mice.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".