Modulatory action of potassium channel openers on field potential and histamine release from rat peritoneal mast cells
Bibliographic record
Abstract
To determine whether changes in membrane potential affect the extent of mast cell degranulation, compound 48/80 was added to rat peritoneal mast cell suspensions in the absence or presence of potassium channel openers (KCOs). Changes were compared between the field potential (FP) and the amount of histamine released. The results demonstrated that (i) the onset and duration of FP, which reflects the hyperpolarizing nature of the response, increased as the concentration of compound 48/80 increased; (ii) both FP and the amount of histamine released increased as the concentration of compound 48/80 increased; (iii) although both KCOs (SDZ PCO400, a benzopyran derivative, and P1060, a cyanoguanidine derivative) potentiated compound 48/80-induced increases in FP and histamine release, without compound 48/80, they had no effect on either parameter; (iv) both glibenclamide and charybdotoxin significantly attenuated the compound 48/80-induced increase in FP; and (v) glibenclamide was able to attenuate the KCO-induced potentiation of FP. The results show that drugs presumably causing hyperpolarization can affect histamine release from rat peritoneal mast cells. The effect of KCOs on compound 48/80-induced response appears to be potentiation in nature rather than synergism. It is possible that KCO hyperpolarizes the cell membrane, enhances Ca2+ influx, and thus increases histamine release. As such, selective blockers of K+ channels may be useful for the treatment of immunological disorders.
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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) | 0.002 | 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".