Mild Therapeutic Hypothermia Does Not Reduce Thrombin-Induced Brain Injury
Bibliographic record
Abstract
Secondary neurodegeneration occurs hours to days after an intracerebral hemorrhage (ICH). Thrombin, a protease important in clotting, is one of the causes of this injury. Presently, we evaluated whether hypothermia mitigates thrombin-induced cerebral edema, cell death, and behavioral impairment. Rats were given a striatal infusion of thrombin, which models thrombin-mediated injury occurring after ICH, followed an hour later by whole-body cooling (33°C), local brain hypothermia (∼ 33°C), or normothermia. Thrombin caused significant edema at 24 hours (∼ 5% increase in water) that was not mitigated by whole-body or brain-selective cooling. Other rats were infused with thrombin and systemically cooled for 72 hours. At a 14-day survival they had similar walking impairments and brain tissue loss (∼ 45 mm(3)) as normothermic rats. However, cooled animals had significantly more degenerating neurons in the peri-lesion zone (p=0.035), which were rare in normothermic rats. Thus, it appears that some cell death was increased or delayed by hypothermia. In summary, we did not find that hypothermia reduced thrombin-induced neurotoxicity. This suggests that cooling does not effectively target thrombin-mediated secondary degeneration after ICH, which may partly explain why cooling is often not robustly neuroprotective in rodent ICH studies. These findings also indicate that therapeutic hypothermia could be improved by the addition of drugs to minimize thrombin toxicity.
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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) | 0.001 | 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".