BDNF expression increases without changes in play behavior following concussion in juvenile rats (<i>Rattus Norvegicus)</i>
Bibliographic record
Abstract
PURPOSE: Young children have a high risk of concussion or mild traumatic brain injury (mTBI). Children often appear healthy soon after mTBI, but some have pervasive cognitive and/or motor impairments. Understanding underlying mechanisms recruited after concussion may help for return to play protocols and mitigating what might be lifelong impairments. METHODS: We investigated molecular and behavioral changes in a rat model of childhood concussion. Rats received an injury or sham procedure at an age approximately equivalent to the human period of early childhood. Social play was analyzed for behavioral differences. Tissue from the right motor cortex (impacted), left motor cortex, and medial prefrontal cortex were analyzed for brain derived neurotrophic factor (BDNF) protein. RESULTS: Play behavior was not significantly different between conditions. BDNF levels were much higher in both the right and left motor cortices of the mTBI group compared to medial prefrontal cortex, which is relatively remote from the impact site, within the mTBI group and all tissue collected from the sham group. CONCLUSIONS: There is ongoing plastic change at the cellular level in both the impacted area and the well-connected contralateral area after a concussion, suggesting compensatory mechanisms after injury are still at play.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".