Repeated mild traumatic brain injury can cause acute neurologic impairment without overt structural damage in juvenile rats
Bibliographic record
Abstract
Repeated concussion is becoming increasingly recognized as a serious public health concern around the world. Moreover, there is a greater awareness amongst health professionals of the potential for repeated pediatric concussions to detrimentally alter the structure and function of the developing brain. To better study this issue, we developed an awake closed head injury (ACHI) model that enabled repeated concussions to be performed reliably and reproducibly in juvenile rats. A neurological assessment protocol (NAP) score was generated immediately after each ACHI to help quantify the cumulative effects of repeated injury on level of consciousness, and basic motor and reflexive capacity. Here we show that we can produce a repeated ACHI (4 impacts in two days) in both male and female juvenile rats without significant mortality or pain. We show that both single and repeated injuries produce acute neurological deficits resembling clinical concussion symptoms that can be quantified using the NAP score. Behavioural analyses indicate repeated ACHI acutely impaired spatial memory in the Barnes maze, and an interesting sex effect was revealed as memory impairment correlated moderately with poorer NAP score performance in a subset of females. These cognitive impairments occurred in the absence of motor impairments on the Rotarod, or emotional changes in the open field and elevated plus mazes. Cresyl violet histology and structural magnetic resonance imaging (MRI) indicated that repeated ACHI did not produce significant structural damage. MRI also confirmed there was no volumetric loss in the cortex, hippocampus, or corpus callosum of animals at 1 or 7 days post-ACHI. Together these data indicate that the ACHI model can provide a reliable, high throughput means to study the effects of concussions in juvenile rats.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 teacher head, 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".