Surface dialysis after experimental brain injury: modification of edema fluid flow in the rat model
Bibliographic record
Abstract
OBJECT: This study was undertaken to determine if dialysis of damaged brain surface can reduce cerebrospinal fluid (CSF) pressure and progressive brain edema. The authors secondarily determined if local brain cooling was simultaneously possible. METHODS: Telemetric pressure transmitters were implanted into the lumbar subarachnoid space of 58 young adult male rats. Cryogenic brain injury was created and 2 hours later decompressive craniectomy was performed. An osmotic cell with a semipermeable dialysis membrane placed on the damaged brain surface was perfused with dextran 15% solution for 2 or 4 hours. Water content was determined in the cerebral hemispheres using the wet-dry weight method. Evans blue-albumin spread was measured morphometrically. Brain temperature was measured bilaterally. RESULTS: The CSF pressure increased after cryogenic injury and decreased after craniotomy. Two hours of brain dialysis significantly reduced CSF pressure in comparison with craniotomy alone and sham dialysis. Injured brain had higher water content, but this was not affected by dialysis. Spread of Evans blue-albumin, however, was significantly reduced by the treatment. Cooling of the dialysis solution caused significant local brain cooling. CONCLUSIONS: Surface dialysis of cryogenically injured rat brain controls CSF pressure and reduces intraparenchymal spread of edema fluid in the acute period after injury. The authors postulate that edema fluid moves into the osmotic cell rather than spreading through the uninjured brain. Long-term experiments will be needed to prove that this combination therapy is effective.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".