Electrical stimulation accelerates and increases expression of BDNF and trkB mRNA in regenerating rat femoral motoneurons
Bibliographic record
Abstract
Electrical stimulation promotes the speed and accuracy of motor axonal regeneration. The positive effects of stimulation are mediated at the cell body. Here we characterize the effect of electrical stimulation on motoneuronal expression of BDNF and its receptor, trkB, two genes whose expression levels in motoneurons correlate with regeneration and are regulated by electrical activity in a variety of neurons. We used semiquantitative in situ hybridization to measure expression of mRNA encoding BDNF and the full-length trkB receptor at intervals of 8 h, 2 days and 7 days after unilateral femoral nerve cut, suture, and stimulation. Expression in regenerating motoneurons was compared to that of contralateral intact motoneurons. BDNF and trkB signals were not significantly upregulated 8 h and 2 days after femoral nerve suture and sham stimulation. By 7 days, there was a 2-fold increase in both BDNF and trkB mRNA expression. In contrast, stimulation of cut and repaired nerves for only 1 h led to rapid upregulation of BDNF and trkB mRNA by 3-fold and 2-fold, respectively, within the first 8 h. The stimulation effect peaked at 2 days with 6-fold and 4-fold increases in the signals, respectively. Thereafter, the levels of BDNF and trkB mRNA expression declined to equal the 2-fold increase seen at 7 days after nerve repair and sham-stimulation. We conclude that brief electrical stimulation stimulates BDNF and trkB expression in regenerating motoneurons. Because electrical stimulation is known to accelerate axonal regeneration, we suggest that changes in the expression of BDNF and trkB correlate with acceleration of axonal regeneration.
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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) | 0.001 | 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".