Sleep deprivation does not affect neuronal susceptibility to mild traumatic brain injury in the rat
Bibliographic record
Abstract
Mild and moderate traumatic brain injuries (TBIs) (and concussion) occur frequently as a result of falls, automobile accidents, and sporting activities, and are a major cause of acute and chronic disability. Fatigue and excessive sleepiness are associated with increased risk of accidents, but it is unknown whether prior sleep debt also affects the pathophysiological outcome of concussive injury. Using the "dark neuron" (DN) as a marker of reversible neuronal damage, we tested the hypothesis that acute (48 hours) total sleep deprivation (TSD) and chronic sleep restriction (CSR; 10 days, 6-hour sleep/day) affect DN formation following mild TBI in the rat. TSD and CSR were administered using a walking wheel apparatus. Mild TBI was administered under anesthesia using a weight-drop impact model, and the acute neuronal response was observed without recovery. DNs were detected using standard bright-field microscopy with toluidine blue stain following appropriate tissue fixation. DN density was low under home cage and sleep deprivation control conditions (respective median DN densities, 0.14% and 0.22% of neurons), and this was unaffected by TSD alone (0.1%). Mild TBI caused significantly higher DN densities (0.76%), and this was unchanged by preexisting acute or chronic sleep debt (TSD, 0.23%; CSR, 0.7%). Thus, although sleep debt may be predicted to increase the incidence of concussive injury, the present data suggest that sleep debt does not exacerbate the resulting neuronal damage.
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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 | 0.001 | 0.000 |
| 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 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".