Temperature-Regulated Model of Focal Ischemia in the Mouse
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The importance of mouse stroke models has increased with the development of genetically manipulated animals. We hypothesized that immediate postischemia hypothermia may attenuate ischemic brain injury in the mouse. METHODS: Intraabdominal radio frequency probes were implanted in animals and core temperature monitored. Groups included: MCAO-45-REG (45 minutes middle cerebral artery occlusion [MCAO]) temperature-controlled in the postischemic period >34 degrees C for 24 hours; MCAO-45 (45 minutes MCAO) were allowed to self-regulate core temperature during recovery; MCAO-30-REG (30 minutes MCAO), with the same temperature protocol as MCAO-45-REG; MCAO-30 (30 minutes MCAO), with temperature protocol the same as MCAO-45. Behavior and histological score was assessed at 7 days. The qualitative histological score assessed for injury in 18 specified regions. RESULTS: MCAO-45-REG core temperature (mean 34.94 degrees C+/-0.8 degrees C) was significantly different than the self-regulating (MCAO-45, mean 33.1 degrees C+/-2.3 degrees C) for the first 4 hours after anesthesia (P<0.01). There was a trend toward similar differences in temperatures for MCAO-30-REG and MCAO-30 (P=0.08). At 7 days, a greater improvement in behavior score was observed for MCAO-45 and MCAO-30 compared with MCAO-45-REG and MCAO-30-REG (P<0.001). The histological score confirmed reduced injury in unregulated temperature groups (MCAO-45-REG mean 38+/-10 and MCAO-45 30+/-5.1, P<0.05; MCAO-30-REG 41+/-10 and MCAO-30 30+/-9, P<0.05). CONCLUSIONS: Hypothermia is an important confounder of stroke injury in the intraluminal filament mouse model. Future mouse stroke studies must use strict temperature regulation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".