Accelerated Ca<sup>2+</sup>entry by membrane hyperpolarization due to Ca<sup>2+</sup>-activated K<sup>+</sup>channel activation in response to histamine in chondrocytes
Bibliographic record
Abstract
In articular cartilage inflammation, histamine release from mast cells is a key event. It can enhance cytokine production and matrix synthesis and also promote cell proliferation by stimulating chondrocytes. In this study, the functional impact of Ca(2+)-activated K(+) (K(Ca)) channels in the regulation of intracellular Ca(2+) concentration ([Ca(2+)](i)) in chondrocytes in response to histamine was examined using OUMS-27 cells, as a model of chondrocytes derived from human chondrosarcoma. Application of histamine induced a significant [Ca(2+)](i) rise and also membrane hyperpolarization, and both effects were mediated by the stimulation of H(1) receptors. The histamine-induced membrane hyperpolarization was attenuated to approximately 50% by large-conductance K(Ca) (BK) channel blockers, and further reduced by intermediate (IK) and small conductance K(Ca) (SK) channel blockers. The tonic component of histamine-induced [Ca(2+)](i) rise strongly depended on the presence of extracellular Ca(2+) ([Ca(2+)](o)) and was markedly reduced by La(3+) or Gd(3+) but not by nifedipine. It was significantly attenuated by BK channel blockers, and further blocked by the cocktail of BK, IK, and SK channel blockers. The K(Ca) blocker cocktail also significantly reduced the store-operated Ca(2+) entry (SOCE), which was induced by Ca(2+) addition after store-depletion by thapsigargin in [Ca(2+)](o) free solution. Our results demonstrate that the histamine-induced membrane hyperpolarization in chondrocytes due to K(Ca) channel activation contributes to sustained Ca(2+) entry mainly through SOCE channels in OUMS-27 cells. Thus, K(Ca) channels appear to play an important role in the positive feedback mechanism of [Ca(2+)](i) regulation in chondrocytes in the presence of articular cartilage inflammation.
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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 | 0.001 | 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".