Long-Term Viral Brain-Derived Neurotrophic Factor Delivery Promotes Spasticity in Rats with a Cervical Spinal Cord Hemisection
Bibliographic record
Abstract
We have recently reported that rats with complete thoracic spinal cord injury (SCI) that received a combinatorial treatment, including viral brain-derived neurotrophic factor (BDNF) delivery in the spinal cord, not only showed enhanced axonal regeneration, but also deterioration of hind-limb motor function. By demonstrating that BDNF over-expression can trigger spasticity-like symptoms in a rat model of sacral SCI, we proposed a causal relationship between the observed spasticity-like symptoms (i.e., resistance to passive range of motion) and the over-expression of BDNF. The current study was originally designed to evaluate a comparable combined treatment for cervical SCI in the rat to improve motor recovery. Once again we found similar signs of spasticity involving clenching of the paws and wrist flexion. This finding changed the focus of the study and, we then explored whether this spasticity-like symptom is directly related to the over-expression of BDNF by administering a BDNF antagonist. Using electromyographic measurements we showed that this treatment gradually diminished the resistance to overcome forelimb flexion in an acute experiment. Thus, we conclude that neuro-excitatory effects of chronic BDNF delivery together with diminished descending control after SCI can result in adverse effects.
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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) | 0.002 | 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".