Cortical electrical stimulation in female rats with a cervical spinal cord injury to promote axonal outgrowth
Bibliographic record
Abstract
Electrical stimulation (ES) to promote corticospinal tract (CST) repair after spinal cord injury (SCI) is underinvestigated. This study is the first to detail intracortical ES of the injured CST. We hypothesize that cortical ES will promote CST collateralization and regeneration, prevent dieback, and improve recovery in an SCI rat model. The CST was transected at the the fourth cervical level in adult female Lewis rats trained in a stairwell grasping task. Animal groups included (a) ES333 (n = 14; 333 Hz, biphasic pulse for 0.2-ms duration every 500 ms, 30 pulses per train); (b) ES20 (n = 14; 20 Hz, biphasic pulse for 0.2-ms duration every 1 s, 60 pulses per train); (c) SCI only (n = 10); and (d) sham (n = 10). ES of the injured forelimb's motor cortex was performed for 30 min immediately prior to SCI. Comparisons between histological data were performed with a 1-way ANOVA or Kruskal-Wallis test, and grasping scores were compared using repeated-measures 2-way ANOVA. Significantly more axonal collateralization was found in ES333 animals compared with controls (p < .01). Axonal dieback analysis revealed ES20 rats to have consistently more dieback than the other groups at all points measured (p < .05). No difference in axonal regeneration was found between groups, nor was there any difference in functional recovery. Cortical ES of the injured CST results in increased collateral sprouting and influences neuroplasticity depending on the ES parameters used. Further investigation regarding optimal parameters and its functional effects is required.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".