Controlled Nerve Ablation With Direct Current: Parameters and Mechanisms
Bibliographic record
Abstract
Spastic hypertonus (muscle over-activity) often develops after spinal cord injury or stroke. Chemodenervating agents such as Botulinum toxin A (BtA) and phenol are often used to treat this condition. We have previously shown that the use of direct current (DC) to create controlled lesions of peripheral nerves may provide a means of reducing spastic hypertonus. Here, we explored a range of stimulation parameters that could be used clinically. Nerves were lesioned with DC in chronically implanted animals and the outcome was tracked over many months. In addition, we used DC to ablate nerves in animals with decerebrate rigidity (an animal model of spastic hypertonus) and we explored the possible mechanisms of DC nerve ablation. We found that nerve ablation with DC was effective in reducing hypertonus. Some stimulation paradigms were more likely to be clinically acceptable than others. Furthermore we showed that nerve regeneration occurs in the months following DC nerve ablation and we demonstrated that the ablation procedure is repeatable, much like BtA treatment. Regarding mechanism, our results did not support the hypothesis that DC caused nerve damage by overactivating sodium channels. Rather, the mechanism of damage seems to be related to changes in pH.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".