Induction of ischemic stroke in awake freely moving mice reveals that isoflurane anesthesia can mask the benefits of a neuroprotection therapy
Bibliographic record
Abstract
Anesthetics such as isoflurane are commonly used to sedate experimental animals during the induction of stroke. Since these agents are known to modulate synaptic excitability, inflammation and blood flow, they could hinder the development and discovery of new neuroprotection therapies. To address this issue, we developed a protocol for inducing photothrombotic occlusion of cerebral vessels in fully conscious mice and tested two potential neuroprotectant drugs (a GluN2B or α4β2 nicotinic receptor antagonist). Our data show in vehicle treated mice that just 20 min of exposure to isoflurane during stroke induction can significantly reduce ischemic cortical damage relative to mice that were awake during stroke. When comparing potential stroke therapies, none provided any level of neuroprotection if the stroke was induced with anesthesia. However, if mice were fully conscious during stroke, the α4β2 nicotinic receptor antagonist reduced ischemic damage by 23% relative to vehicle treated controls, whereas the GluN2B antagonist had no significant effect. These results suggest that isoflurane anesthesia can occlude the benefits of certain stroke treatments and warrant caution when using anesthetics for pre-clinical testing of neuroprotective agents.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".