Sensitivity to Sevoflurane anesthesia is decreased in mice with a congenital deletion of Guanylyl Cyclase-1 alpha
Bibliographic record
Abstract
Volatile anesthetics increase levels of the neurotransmitter nitric oxide (NO) and the secondary messenger molecule cyclic guanosine monophosphate (cGMP) in the brain. NO activates the enzyme guanylyl cyclase (GC) to produce cGMP. We hypothesized that the NO-GC-cGMP pathway contributes to anesthesia-induced unconsciousness. Sevoflurane-induced loss and return of righting reflex (LORR and RORR, respectively) were studied in wild-type mice (WT) and in mice congenitally deficient in the GC-1α subunit (GC-1 −/− mice). Spatial distributions of GC-1α and the GC-2α subunit in the brain were visualized by in situ hybridization. Brain cGMP levels were measured in WT and GC-1 −/− mice after inhaling oxygen with or without 1.2% sevoflurane for 20 min. Higher concentrations of sevoflurane were required to induce LORR in GC-1 −/− mice than in WT mice (1.5 ± 0.1 vs. 1.1 ± 0.2%, respectively, n = 14 and 14, P < 0.0001). Similarly, RORR occurred at higher concentrations of sevoflurane in GC-1 −/− mice than in WT mice (1.0 ± 0.1 vs. 0.8 ± 0.1%, respectively, n = 14 and 14, P < 0.0001). Abundant GC-1α and GC-2α mRNA expression was detected in the cerebral cortex, medial habenula, hippocampus, and cerebellum. Inhaling 1.2% sevoflurane for 20 min increased cGMP levels in the brains of WT mice from 2.6 ± 2.0 to 5.5 ± 3.7 pmol/mg protein ( n = 13 and 10, respectively, P = 0.0355) but not in GC-1 −/− mice. Congenital deficiency of GC-1α abolished the ability of sevoflurane anesthesia to increase cGMP levels in the whole brain, and increased the concentration of sevoflurane required to induce LORR. Impaired NO-cGMP signaling raises the threshold for producing sevoflurane-induced unconsciousness in 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".