Neurodevelopmental Impacts of Ketamine and Alfaxalone Anesthesia Evaluated with Mouse MRI
Bibliographic record
Abstract
Injectable anesthetics are commonly used in murine experimental procedures. However, these agents may result in neurotoxicity, which should be considered in interpretation of experimental results. We evaluated acute effects of 2 different anesthetic combinations on juvenile mouse brain development using structural MRI to assess impact on the brain. We compared the use of ketamine-xylazine, a commonly used injectable anesthetic combination in mice, to alfaxalone-xylazine in the context of noninvasive procedures requiring immobilization (that is, not a surgical plane of anesthesia). In this longitudinal study, we used MRI to produce three-dimensional scans of mouse brains at 2 time points (postnatal days 14 and 23), analogous to early childhood to prepubescence in humans. At postnatal day 16, mice were either dosed with ketamine-xylazine, alfaxalone-xylazine, or left untreated. From the scans, we quantified whole brain and structure volumes across the brain, comparing growth between time points and modeling the effect of both anesthetics compared with controls. Anesthetic parameters were measured, and general health and welfare were monitored during and after each injectable anesthesia drug condition. Results indicate that systemic and brain toxicity were reduced in mice treated with alfaxalone-xylazine compared with ketamine-xylazine. In addition, both ketamine-xylazine and alfaxalone-xylazine reliably anesthetized all mice, although mice administered ketamine-xylazine showed increased weight loss compared with the alfaxalone-xylazine in the postanesthetic period. These findings highlight alfaxalone-xylazine as a convenient and possibly safer alternative anesthetic for mouse brain development studies when compared with ketamine-xylazine and as a viable option as an injectable anesthetic in juvenile mice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".