Tau hyperphosphorylation induced by the anesthetic agent ketamine/xylazine involved the calmodulin‐dependent protein kinase II
Bibliographic record
Abstract
Tau hyperphosphorylation is a major neuropathological hallmark of many neurodegenerative disorders such as Alzheimer's disease. Several anesthetics have been shown previously to induced marked tau hyperphosphorylation. Although the ketamine/xylazine mixture is one of the most commonly used anesthetic agents in animal research and veterinary practice, the effect of this anesthetic agent on tau phosphorylation still remains to be determined. Here, we found that ketamine-/xylazine-induced a rapid and robust hyperphosphorylation of tau in a dose-dependent manner under normothermic and hypothermic conditions in mice. When used together, ketamine and xylazine exerted a synergistic action on tau phosphorylation most strongly not only on epitopes S396 and S262, but also on other residues (T181, and S202/T205). We observed that activation of the calmodulin-dependent protein kinase II (CaMKII) is the major upstream molecular event leading to tau hyperphosphorylation following ketamine/xylazine anesthesia in mice. Moreover, we observed that intracerebroventricular injection of the selective CaMKII inhibitor KN93 attenuated tau hyperphosphorylation. Since ketamine/xylazine also had a marked impact on other key molecular signaling pathways involving the MAP/microtubule affinity-regulating kinase (MARK), extracellular signal-regulated kinase (ERK), and glycogen synthase kinase-3 (GSK3), our study calls for high caution and careful monitoring when using this anesthetic agent in laboratory animal settings across all fields of biological sciences in order to avoid artifactual results.
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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) | 0.000 | 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".