Matrix metalloproteinase 3 deletion preserves denervated motor endplates after traumatic nerve injury
Bibliographic record
Abstract
OBJECTIVE: Traumatic peripheral nerve injuries often produce permanent functional deficits despite optimal surgical and medical management. One reason for the impaired target organ reinnervation is degradation of motor endplates during prolonged denervation. Here we investigate the effect of preserving agrin on the stability of denervated endplates. Because matrix metalloproteinase 3 (MMP3) is known to degrade agrin, we examined the changes in endplate structure following traumatic nerve injury in MMP3 knockout mice. METHODS: After creation of a critical size nerve defect to preclude reinnervation, we characterized receptor area, receptor density, and endplate morphology in denervated plantaris muscles in wild-type and MMP3 null mice. The level of agrin and muscle-specific kinase (MuSK) was assessed at denervated endplates. In addition, denervated muscles were subjected to ex vivo stimulation with acetylcholine. Finally, reinnervation potential was compared after long-term denervation. RESULTS: In wild-type mice, the endplates demonstrated time-dependent decreases in area and receptor density and conversion to an immature receptor phenotype. In striking contrast, all denervation-induced changes were attenuated in MMP3 null mice, with endplates retaining their differentiated form. Agrin and MuSK were preserved in endplates from denervated MMP3 null animals. Furthermore, denervated muscles from MMP3 null mice demonstrated greater endplate efficacy and reinnervation. INTERPRETATION: These results demonstrate a critical role for MMP3 in motor endplate remodeling, and reveal a potential target for therapeutic intervention to prevent motor endplate degradation following 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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".