Enhanced Tonic Inhibition Influences the Hypnotic and Amnestic Actions of the Intravenous Anesthetics Etomidate and Propofol
Bibliographic record
Abstract
Intravenous anesthetics exert a component of their actions via potentiating inhibitory neurotransmission mediated by γ-aminobutyric type-A receptors (GABAARs). Phasic and tonic inhibition is mediated by distinct populations of GABAARs, with the majority of phasic inhibition by subtypes composed of α1-3βγ2 subunits, whereas tonic inhibition is dependent on subtypes assembled from α4-6βδ subunits. To explore the contribution that these distinct forms of inhibition play in mediating intravenous anesthesia, we have used mice in which tyrosine residues 365/7 within the γ2 subunit are mutated to phenyalanines (Y365/7F). Here we demonstrate that this mutation leads to increased accumulation of the α4 subunit containing GABAARs in the thalamus and dentate gyrus of female Y365/7F but not male Y365/7F mice. Y365/7F mice exhibited a gender-specific enhancement of tonic inhibition in the dentate gyrus that was more sensitive to modulation by the anesthetic etomidate, together with a deficit in long-term potentiation. Consistent with this, female Y365/7F, but not male Y365/7F, mice exhibited a dramatic increase in the duration of etomidate- and propofol-mediated hypnosis. Moreover, the amnestic actions of etomidate were selectively potentiated in female Y365/7F mice. Collectively, these observations suggest that potentiation of tonic inhibition mediated by α4 subunit containing GABAARs contributes to the hypnotic and amnestic actions of the intravenous anesthetics, etomidate and propofol.
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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".