Releasing ‘brakes’ to nerve regeneration: intrinsic molecular targets
Bibliographic record
Abstract
Restoring critical neuronal architecture after peripheral nerve injury is challenging. Although immediate regenerative responses to peripheral axon injury involve the synthesis of regeneration-associated proteins in neurons and Schwann cells, an unfavorable balance between growth facilitatory and growth inhibitory signaling impairs the growth continuum of injured peripheral nerves. Molecules involved with the signaling network of tumor suppressors play crucial roles in shifting the balance between growth and restraint during axon regeneration. An understanding of the molecular framework of tumor suppressor molecules in injured neurons and its impact on stage-specific regeneration events may expose therapeutic intervention points. In this review we discuss how signaling networks of the specific tumor suppressors PTEN, Rb1, p53, p27 and p21 are altered in injured peripheral nerves and how this impacts peripheral nerve regeneration. Insights into the roles and importance of these pathways may open new avenues for improving the neurological deficits associated with nerve injury.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".