Brief Electrical Stimulation Promotes Nerve Regeneration Following Experimental In-Continuity Nerve Injury
Bibliographic record
Abstract
BACKGROUND: Brief electrical stimulation (ES) therapy to the nerve may improve outcome in lacerated, repaired nerves. However, most human nerve injuries leave the nerve in continuity with variable and often poor functional recovery from incomplete axon regeneration and reinnervation. OBJECTIVE: To evaluate the effect of brief ES in an experimental model for neuroma-in-continuity (NIC) injuries in rodents. METHODS: Lewis rats were randomly assigned to 1 of 4 groups: NIC injury immediately followed by brief (1 h) ES; NIC injury without ES; sham-operated controls; sciatic nerve transection without repair. Outcome measures included serial behavioral evaluation and electrophysiology together with terminal retrograde spinal cord motor neuron labeling and histomorphological analysis for axonal regeneration. RESULTS: Applying brief ES immediately after in-continuity nerve injury resulted in earlier recovery and significantly improved locomotion function at 4 and 6 wk. At 8 wk, brief ES resulted in higher compound action potential amplitude. By 12 wk there was no significant difference between the 2 groups in behavior or electrophysiology. Histomorphological analysis demonstrated a significantly higher percentage of neural tissue in the brief ES group. Spinal cord motor neuron pool cell counts revealed a preference for regeneration into a motor over a sensory nerve, for the group receiving ES. CONCLUSION: The application of brief ES for in-continuity nerve injury promotes faster recovery, although in a rat model where regeneration distances are short the control group ultimately recovers to a similar degree. Brief EF requires further evaluation as a promising therapy for in-continuity nerve injuries in humans.
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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) | 0.000 | 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) | 0.002 | 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".