CRH Acts on CRH-R1 and -R2 to Differentially Modulate the Expression of Large-Conductance Calcium-Activated Potassium Channels in Human Pregnant Myometrium
Bibliographic record
Abstract
CRH has been implicated to play a key role in the control of human pregnancy and parturition. Large-conductance potassium channels (BKCa) play a pivotal role in the modulation of uterine contractility during pregnancy. The objectives of the present study were to investigate the effect of CRH on BKCa expression in human pregnant myometrial cells. Myometrial tissues were collected at cesarean section from pregnant women not-in-labor (TNL) or in-labor (TL) at term, and myocytes were isolated and cultured. CRH was identified in human pregnant myometrium and mainly expressed in myometrial myocytes. Cultured myometrial cells were able to secrete CRH. In TNL myometrial cells, CRH treatment increased the expression of BKCa α- and β-subunits. CRH receptor type 1 (CRH-R1) antagonist, antalarmin, decreased whereas CRH receptor type 2 (CRH-R2) antagonist, astressin2b, increased the expression of BKCa. CRH-R2 small interfering RNA (siRNA) caused an increase, but CRH-R1 siRNA resulted in a decrease, in BKCa expression. In contrast to TNL cells, CRH exhibited an opposite effect on BKCa expression in TL myometrial cells, i.e. decreased BKCa expression. Antalarmin enhanced but astressin2b reduced BKCa expression. CRH-R2 siRNA decreased whereas CRH-R1 siRNA increased BKCa expression. 1,3-Dihydro-1-[2-hydroxy-5-(trifluoromethyl)phenyl]-5-(trifluoromethyl)-2H-benzimidazol-2-one significantly inhibited the frequency of spontaneous contractions of myometrial strips, and this effect was significantly decreased in TL strips compared with TNL ones. Our data suggest that CRH-R1 and CRH-R2 show differential regulation of BKCa expression. These effects mediated by CRH-R1 and CRH-R2 are changed after the onset of labor. This leads us to suggest that CRH may fine-tune myometrial contractility by modulating the expression of BKCa during pregnancy and labor.
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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 | 0.001 |
| 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".