Effect of Brain-Derived Neurotrophic Factor, Nerve Growth Factor, and Neurotrophin-3 on Functional Recovery and Regeneration After Spinal Cord Injury in Adult Rats
Bibliographic record
Abstract
This study examined whether continuous intramedullary infusion of brain-derived neurotrophic factor (BDNF), nerve growth factor (NGF), or neurotrophin-3 (NT-3) had either an early neuroprotective effect or a delayed effect on regeneration after spinal cord injury (SCI) in adult rats. BDNF, NGF, NT-3 or vehicle was infused at a rate of 625 ng/h into the SCI site at T3 through an implanted cannula attached to an osmotic pump. This infusion was maintained for 14 days after a 35-g clip compression injury. At 4 weeks after injury, the axonal tracer fluorogold (FG) was introduced into the spinal cord caudal to the lesion and the animals sacrificed 3 days later following behavioral assessment. The inclined plane score was significantly higher in BDNF-treated animals (45 +/- 3 degrees) compared to control animals (36 -/+ 1 degrees) at 1 week after injury (p < 0.05), although the scores were not significantly different at later times. BDNF-treated animals also showed more FG-labeled cells in the red nucleus and sensorimotor cortex (1,638 +/- 350 and 124 +/- 83, respectively) compared to controls (1,228 +/- 217 and 36 +/- 15, respectively) and a lower percent cavitation at the injury site (21.4 +/- 10.4%) compared to control animals (32.3 +/- 11.7%). Invasion & proliferation of Schwann cells and formation of peripheral myelin were more prominent at the injury site in the BDNF-treated animals than in the other groups. These results indicate that continuous intramedullary infusion of BDNF provides neuroprotection and enhances some regenerative activity after SCI.
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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) | 0.000 | 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 | 0.001 |
| 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".