Inhibition of small-conductance Cl- channels by the interleukin-1beta-stimulated production of superoxide in rabbit gastric parietal cells
Bibliographic record
Abstract
We have shown previously that the G protein-coupled production of superoxide anion (O2-) leads to closure of small-conductance Cl- channels (0.3-0.4 pS) in the basolateral membrane of rabbit parietal cells. In the present study, effects of interleukin-1beta (IL-1beta) on the Cl- channel were investigated. In the whole-cell patch-clamp recording, IL-1beta (0.3-10 ng ml-1) inhibited the whole-cell Cl- current recorded from a parietal cell within isolated rabbit gastric glands. Variance noise analysis of the whole-cell Cl- current showed that the single channel conductance of the Cl- channel that is sensitive to IL-1beta is 0.37 pS. The IL-1beta (1 ng ml-1)-induced decrease of the Cl- current was abolished by anti-IL-1beta antibody (2 microg ml-1), recombinant IL-1 receptor antagonist (500 ng ml-1), GDPbetaS (500 microM) and superoxide dismutase (100 units ml-1), a scavenger of O2-. Northern blot analysis showed that the mRNA of the IL-1 receptor was selectively expressed in rabbit gastric parietal cells. In the dihydrofluorescein diacetate-loaded single parietal cells in gastric glands, IL-1beta (0.3-10 ng ml-1) stimulated the production of oxygen radicals. Y-27632 (1-10 microM), a specific Rho-kinase inhibitor, and fluvastatin (10 microM), an indirect inhibitor for Rho proteins, significantly inhibited the IL-1beta-induced effects on the channel activity and production of oxygen radicals. IL-1beta (0.3-10 ng ml-1) activated Rho in the parietal cells. These results indicate that IL-1beta binds to the IL-1 receptor of gastric parietal cells and inhibits the small-conductance Cl- channel via the G protein-mediated Rho/Rho-kinase-dependent production of O2-.
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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".