Assessment of an Experimental Rodent Model of Pediatric Mild Traumatic Brain Injury
Bibliographic record
Abstract
Childhood is one the highest risk periods for experiencing a mild traumatic brain injury (mTBI) from sports-related concussions, motor vehicle accidents, and falls. In addition, many children experience lingering symptomology (post-concussion syndrome) from these closed head injuries. Although the negative sequel of mTBI has been described, a clinically reliable animal model of mild pediatric brain injury has not. The purpose of this study was to examine the validity of a modified weight-drop technique as a model for the induction of mTBI/concussion in juvenile rats following a single impact. Male and female rats (P30) were exposed to a single mTBI or a sham injury followed by a behavioral test battery. Juvenile rats who experienced a single mTBI displayed significant motor/balance impairments when tested on the beam walking task and in the open field, as well as deficits of executive functioning as measured with the novel context mismatch task and the probe trial of the Morris water task. In addition, both male and female rats showed depression-like behavior in the forced swim task, with male rats also exhibiting decreased anxiety-related behaviors in the elevated plus maze. The results from this study suggest that the modified weight-drop technique induces a clinically relevant behavioral phenotype in juvenile rats, and may provide researchers with a reliable animal model of mTBI/concussion from which clinical therapeutic strategies could be developed.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".