Effects of hemodilution after traumatic brain injury in juvenile rats
Bibliographic record
Abstract
BACKGROUND: Normovolemic hemodilution (HD) in adult animal studies has shown exacerbation of traumatic brain injury (TBI) lesion volumes. Similar studies in juvenile rats have not been reported and outcomes are likely to be different. This study investigated the effects of normovolemic hemodilution (21% hematocrit) in a juvenile TBI (jTBI) model. METHODS: Twenty 17-day-old rats underwent moderate cortical contusion impact injury (CCI) and were divided into four groups: CCI/hemodilution (HD) (group HD), CCI/no HD (group C), Sham/HD (group SHD), and Sham/no HD (group S). Regional laser Doppler flowmetry (LDF), edema formation (MRI-T2WI), water mobility assessed using diffusion weighted imaging (MRI-DWI), open field activity tests, and histological analyses were evaluated for lesion characteristics. RESULTS: Hemodilution significantly increased blood flow in the HD compared to the C group after TBI. T2WI revealed a significantly increased extravascular blood volume in HD at 1, 7, and 14 days post-CCI. Edematous tissue and total contusional lesion volume were higher in HD-treated animals at 1 and 14 days. DWI revealed that HD, SHD, and C groups had elevated water mobility compared to S groups in the ipsilateral cortex and striatum. Histology showed a larger cortical lesion in the C than HD group. Open field activity was increased in HD, C, and SHD groups compared to the S group. CONCLUSIONS: Hemodilution results in significant brain hyperemia with increased edema formation, extravascular blood volume, and water mobility after jTBI. Hemodilution results in less cortical damage but did not alter behavior. Hemodilution is likely not to be clinically beneficial following jTBI.
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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 | 0.000 |
| 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".