Contribution of the Distal Nerve Sheath to Nerve and Muscle Preservation Following Denervation and Sensory Protection
Bibliographic record
Abstract
The goal of this study was to determine the contribution of the distal nerve sheath to sensory protection. Following tibial nerve transection, rats were assigned to one of the following groups: (1) saphenous-to-tibial nerve neurorrhaphy; (2) saphenous-to-gastrocnemius neurotization; (3) unprotected controls (tibial nerve transection); or (4) immediate common peroneal-to-tibial nerve neurorrhaphy. After a 6-month denervation period and motor reinnervation, ultrastructural, histologic, and morphometric analyses were performed on the distal tibial nerve and gastrocnemius muscle cross-sections. Sensory axons neurotized to muscle maintain existing muscle integrity, as demonstrated by less fibrosis, collagenization, and fat deposition, more than unprotected muscle, and preserve the distribution pattern of fast twitch fibers. However, neurorrhaphy of the sensory nerve to the distal tibial nerve (involving the distal nerve sheath) improves existing endoneurial sheath structure, demonstrated by reduced collagen, and enhances regeneration, shown by improved axon-to-Schwann cell coupling and increased axon area. The authors conclude that sensory protection of muscle does not require the distal nerve sheath, but that preservation of the distal sheath may contribute to enhanced nerve regeneration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".