Behavioural and anatomical analysis of selective tibial nerve branch transfer to the deep peroneal nerve in the rat
Bibliographic record
Abstract
Nerve transfer procedures involving the repair of a distal denervated nerve element with that of a foreign proximal nerve have become increasingly popular for clinical nerve repair as a surgical alternative to autologous nerve grafting. However, the functional outcomes and the central plasticity for these procedures remain poorly defined, particularly for a clinically relevant rodent model of hindlimb nerve transfer. We therefore evaluated the effect of selective tibial branch nerve transfer on behavioural recovery in animals following acute transection of the deep peroneal nerve. The results indicate that not only can hindlimb nerve transfers be successfully accomplished in a rat model but that these animals display a return of skilled locomotor function on a par with animals that underwent direct deep peroneal nerve repair (the current gold standard). At 2 months, ground reaction force analysis demonstrated that partial restoration of braking forces occurred in the nerve transfer group, whereas the direct repair group had fully restored these forces to similar to baseline levels. Ankle kinematic analysis revealed that only animals in the direct repair group significantly recovered flexion during the step cycle, indicating a recovery of surgically induced foot drop. Terminal electrophysiological and myological assessments demonstrated similar levels of reinnervation, whereas retrograde labelling studies confirmed that the peroneal nerve-innervated muscles were innervated by neurons from the tibial nerve pool in the nerve transfer group. Our results demonstrate a task-dependent recovery process, where skilled locomotor recovery is similar between nerve transfer and direct repair animals, whereas flat surface locomotion is significantly better in direct repair animals.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".