Protease-activated receptor-1 stimulates Ca<sup>2+</sup>-dependent Cl<sup>−</sup>secretion in human intestinal epithelial cells
Bibliographic record
Abstract
The thrombin receptor, protease-activated receptor-1 (PAR-1), has wide tissue distribution and is involved in many physiological functions. Because thrombin is in the intestinal lumen and mucosa during inflammation, we sought to determine PAR-1 expression and function in human intestinal epithelial cells. RT-PCR showed PAR-1 mRNA expression in SCBN cells, a nontransformed duodenal epithelial cell line. Confluent SCBN monolayers mounted in Ussing chambers responded to PAR-1 activation with a Cl(-)-dependent increase in short-circuit current. The secretory effect was blocked by BaCl2 and the Ca(2+)-ATPase inhibitor thapsigargin, but not by the L-type Ca(2+) channel blocker verapamil or DIDS, the nonselective inhibitor of Ca(2+)-dependent Cl(-) transport. Responses to thrombin and PAR-1-activating peptides exhibited auto- and crossdesensitization. Fura 2-loaded SCBN cells had increased fluorescence after PAR-1 activation, indicating increased intracellular Ca(2+). RT-PCR showed that SCBN cells expressed mRNA for the cystic fibrosis transmembrane conductance regulator (CFTR) and hypotonicity-activated Cl(-) channel-2 but not for the Ca(2+)-dependent Cl(-) channel-1. PAR-1 activation failed to increase intracellular cAMP, suggesting that the CFTR channel is not involved in the Cl(-) secretory response. Our data demonstrate that PAR-1 is expressed on human intestinal epithelial cells and regulates a novel Ca(2+)-dependent Cl(-) secretory pathway. This may be of clinical significance in inflammatory intestinal diseases with elevated thrombin levels.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".