Etomidate Targets α5γ-Aminobutyric Acid Subtype A Receptors to Regulate Synaptic Plasticity and Memory Blockade
Bibliographic record
Abstract
BACKGROUND: The memory-blocking properties of general anesthetics have recently received considerable attention because of concerns related to intraoperative awareness and postoperative cognitive dysfunction. The goal of this study was to identify the mechanisms by which gamma-aminobutyric acid subtype A receptors that contain the alpha5 subunit (alpha5GABAARs) induce memory-blockade by etomidate and a pharmacologic strategy to reverse this impairment. METHODS: The effects of etomidate and the alpha5GABAAR-preferring inverse agonist L-655,708 on the plasticity of glutamatergic excitatory transmission in hippocampal slices and behavioral memory for spatial navigational and fear-associated memory tasks were studied in wild-type and null mutant mice for the gene that encodes the alpha5 subunit (Gabra5-/- mice). Long-term potentiation of field excitatory postsynaptic potentials was induced in CA1 pyramidal neurons following high-frequency stimulation of Schaffer collaterals. Memory performance was studied in contextual, cued, and trace fear conditioning assays and the Morris water maze. RESULTS: Robust synaptic plasticity induced by high-frequency stimulation and memory performance for contextual fear and spatial navigational memory were not influenced by a decrease in the function of alpha5GABAARs. Nevertheless, etomidate, via an increase in alpha5GABAAR activity, completely blocked long-term potentiation and impaired memory performance, and these effects were reversed by pretreatment with L-655,708. CONCLUSIONS: The results provide the first proof of concept that memory blockade by a general anesthetic can be reversed by inhibiting the function of alpha5GABAARs. The findings suggest a mechanism and model for awareness during anesthesia.
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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) | 0.000 | 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 | 0.000 |
| 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".