Staying in the game: a pilot study examining the efficacy of protective headgear in an animal model of mild traumatic brain injury (mTBI)
Bibliographic record
Abstract
PRIMARY OBJECTIVE: Rugby is one of the few contact sports that do not mandate protective headgear, possibly because studies have shown poor efficacy for protection related to concussion pathology with existing headguards. RESEARCH DESIGN: Following innovative material technology utilization to produce headgear believed to have protective capabilities, this study examined the effects of a soft-shell headgear constructed from a novel viscoelastic material, on both behaviour and serum biomarkers after high and average impact force mild traumatic brain injuries (mTBI). METHODS AND PROCEDURES: Seventy-five male Sprague Dawley rats were divided into five groups: control, average - 37G impact, with and without headgear, and high - 106G impact, with and without headgear. Rats were sacrificed at 3 or 48 hours and serum samples were analyzed for levels of TNF-α, NEF-L, and GFAP. Animals sacrificed at 48 hours also underwent testing for balance and motor coordination, and exploratory/locomotor behaviour. MAIN OUTCOMES AND RESULTS: The novel headgear offered significant protection against mTBI symptomology and biomarkers in the group that experienced an average impact force, but only moderated protection for the animals in the high impact group. CONCLUSIONS: This innovative headgear may prevent some of the negative sequel associated with concussion pathology.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".