Mouse isoflurane anesthesia using the drop method
Bibliographic record
Abstract
Anesthesia with isoflurane prior to carbon dioxide euthanasia is recommended as a refinement, but vaporizer access can be limited. An alternative to vaporizers is the ‘drop’ method, introducing a fixed volume of isoflurane into the induction chamber. Previous work suggests that isoflurane administered at a concentration of 5% via the drop method is effective but aversive to mice; lower concentrations have not been tested. We assessed mouse behavior and insensibility with induction using the drop method for isoflurane concentrations below 5%. Male Crl:CD-1 (ICR) mice ( n = 27) were randomly allocated to one of three isoflurane concentrations: 1.7%, 2.7%, and 3.7%. During induction, measures of insensibility and stress-related behaviors were recorded. All mice reached a surgical plane of anesthesia, and mice exposed to higher concentrations did so more quickly; as concentrations increased from 1.7 to 2.7 and 3.7%, the time to recumbency (Least squares means ± SE: 120.5 s ± 8.1, 97.9 s ± 8.1, and 82.8 s ± 8.1, respectively), loss of righting reflex (149.1 s ± 8.5, 127.7 s ± 8.5, and 100.7 s ± 8.5, respectively), and loss of pedal withdrawal reflex (214.5 s ± 8.3, 172.2 s ± 8.3, and 146.4 s ± 8.3, respectively) all declined. Rearing was the most frequently performed stress-related behavior, and was most pronounced immediately following isoflurane administration for all treatments. Our results indicate that the drop method can be used to effectively anesthetize mice with isoflurane concentrations as low as 1.7%; future work should assess mouse aversion.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.024 | 0.012 |
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".