Isoflurane Regulates Atypical Type-A γ-Aminobutyric Acid Receptors in Alveolar Type II Epithelial Cells
Bibliographic record
Abstract
BACKGROUND: Volatile anesthetics act primarily through upregulating the activity of γ-aminobutyric acid type A (GABAA) receptors. They also exhibit antiinflammatory actions in the lung. Rodent alveolar type II (ATII) epithelial cells express GABAA receptors and the inflammatory factor cyclooxygenase-2 (COX-2). The goal of this study was to determine whether human ATII cells also express GABAA receptors and whether volatile anesthetics upregulate GABAA receptor activity, thereby reducing the expression of COX-2 in ATII cells. METHODS: The expression of GABAA receptor subunits and COX-2 in ATII cells of human lung tissue and in the human ATII cell line A549 was studied with immunostaining and immunoblot analyses. Patch clamp recordings were used to study the functional and pharmacological properties of GABAA receptors in cultured A549 cells. RESULTS: ATII cells in human lungs and cultured A549 cells expressed GABAA receptor subunits and COX-2. GABA induced currents in A549 cells, with half-maximal effective concentration of 2.5 µM. Isoflurane (0.1-250 µM) enhanced the GABA currents, which were partially inhibited by bicuculline. Treating A549 cells with muscimol or with isoflurane (250 µM) reduced the expression of COX-2, an effect that was attenuated by cotreatment with bicuculline. CONCLUSIONS: GABAA receptors expressed by human ATII cells differ pharmacologically from those in neurons, exhibiting a higher affinity for GABA and lower sensitivity to bicuculline. Clinically relevant concentrations of isoflurane increased the activity of GABAA receptors and reduced the expression of COX-2 in ATII cells. These findings reveal a novel mechanism that could contribute to the antiinflammatory effect of isoflurane in the human lung.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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; both teacher heads agree on what is shown here.
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".