The Influence of Hypothermia on Outcome After Intracerebral Hemorrhage in Rats
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Late hypothermia (HYPO) reduces injury after collagenase-induced intracerebral hemorrhage (ICH), whereas early HYPO does not because it exacerbates the protracted bleeding that occurs in this model. We hypothesized that early HYPO would not increase bleeding after whole blood infusion and thus expected early HYPO to improve outcome through reducing secondary consequences of ICH (eg, inflammation). METHODS: Autologous blood (100 microL) was infused into the striatum. Rats were maintained at normothermia or subjected to mild (33 degrees C to 35 degrees C) HYPO for 2 days starting 1 (HYPO-1) or 4 hours (HYPO-4) after ICH. Hematoma volume was measured at 12 hours to determine whether HYPO-1 aggravated bleeding. We measured blood-brain barrier (BBB) disruption and edema 2 days after ICH in all groups. At 4 days, we counted degenerating neurons, neutrophils, and iron-positive cells (eg, macrophages) in the lesioned hemisphere. Recovery was assessed using several behavioral tests (ie, staircase reaching task, ladder walking task, limb use cylinder test) over 7 or 30 days, at which time we quantified lesion volume. RESULTS: HYPO did not increase bleeding. Both HYPO treatments reduced BBB disruption and infiltration of inflammatory cells. HYPO-1 treatment modestly reduced edema and provided limited to no functional benefit in the behavioral tests. HYPO did not affect lesion volume. CONCLUSIONS: HYPO reduced edema, BBB disruption, and inflammation. Although encouraging, HYPO treatment must be improved so that histological and functional benefit are obtained before clinical investigation. Otherwise clinical failure is anticipated.
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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 | 0.000 | 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".