CRYAB plays a role in terminating the presence of pro-inflammatory macrophages in the older, injured mouse peripheral nervous system
Bibliographic record
Abstract
Evidence indicates that dysfunction of older Schwann cells and macrophages contributes to poor regeneration of more mature peripheral nervous system (PNS) neurons after damage. Since the underlying molecular factors are largely unknown, we investigated if CRYAB, a small heat shock protein that is expressed by Schwann cells and axons and whose expression declines with age, impacts prominent deficits in the injured, older PNS including down-regulation of cholesterol biosynthesis enzyme genes, Schwann cell dysfunction, and macrophage persistence. Following sciatic nerve transection injury in 3- and 12-month-old wildtype and CRYAB knockout mice, we found by bulk RNA sequencing and RT-PCR, that while gene expression of cholesterol biosynthesis enzymes is markedly dysregulated in the aging, injured PNS, CRYAB is not involved. However, immunohistochemical staining of crushed sciatic nerves revealed that more macrophages of the pro-inflammatory but not immunosuppressive phenotype persisted in damaged 12-month-old knockout nerves. These pro-inflammatory macrophages were more efficient at engulfing myelin debris. CRYAB thus appears to play a role in resolving pro-inflammatory macrophage responses after damage to the older PNS.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".