A Bump on the Head or Late to Bed: Behavioral and Pathophysiological Effects of Sleep Deprivation after Repetitive Mild Traumatic Brain Injury in Adolescent Rats
Bibliographic record
Abstract
An old wives' tale, and strongly held dogma, maintains that one should be kept awake after a mild traumatic brain injury (mTBI) to prevent a coma. This, however, conflicts with the known benefits of sleep: repair and restoration. We therefore sought to examine the effects of sleep deprivation (SD) in the post-traumatic sleep period on post-concussion symptomology (PCS). Adolescent male and female rats were administered repetitive mTBIs (RmTBI) or sham injuries and were then assigned to 5 h of SD or left undisturbed. All animals were then tested using seven behavioral tasks validated to examine PCS, followed by analysis of serum cytokines, and quantitative real-time PCR for messenger RNA (mRNA) expression. Exposure to 3 SD epochs significantly impaired behavior in 4 of 7 of the measures, while RmTBI also produced dysfunction in 5 of 7 tests, but the effects of SD and RmTBI were not cumulative. SD induced long-lasting changes in serum levels of Tnf-α, IL6, and IL-1ß. mRNA expression in the pre-frontal cortex, hippocampus, hypothalamus, and anterior cingulate cortex was modified in response to SD and RmTBI; but similar to the behavioral measures, the mRNA changes were not cumulative. Consequently, we report that SD often produced impairments similar or worse than RmTBI, and sleep hygiene should become a priority for adolescent health.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.001 | 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 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".