Effects of PGF2α on the Expression of Uterine Activation Proteins in Pregnant Human Myometrial Cells From Upper and Lower Segment
Bibliographic record
Abstract
CONTEXT: The lower and upper segments of the uterus may play different roles in the process of parturition. The switch from pregnancy to delivery involves changes in expression of uterine activation proteins (UAPs). Prostaglandin (PG) F2α has multiple and complex roles in the birth process in addition to its vital contractile role. OBJECTIVE: The purpose of this study was to investigate whether PGF2α regulates the expression of UAPs in human myometrium and to compare PGF2α actions in lower and upper segments. DESIGN: Cultured human myometrial cells from upper and lower segments were treated with PGF2α. Western blotting was used to determine the levels of connexin 43 (CX-43), prostaglandin endoperoxide synthase-2 (PTGS-2; cyclooxygenase-2), oxytocin receptor (OTR), and PGF2α receptor (PTGFR) in the cells. The small interfering RNA approach was used to knock down PTGFR. RESULTS: PGF2α dose dependently increased CX-43 and PTGS-2 while decreasing PTGFR in upper and lower segments. PGF2α increased OTR in the lower segment while decreasing it in the upper segment. PGF2α lost its effects on PTGS-2 and OTR in PTGFR knockdown cells, but its effect on CX-43 remained. AL8810, a specific antagonist of PTGFR, reversed the actions of PGF2α on UAPs except for CX-43 in the lower segment. Indomethacin reversed the PGF2α-induced effects on CX-43 and PTGS-2, but it did not alter PGF2α-induced PTGFR and OTR expression. The stimulatory effects of PGF2α were enhanced in the presence of IL-1β, which reversed the inhibitory effect of PGF2α on PTGFR. CONCLUSION: PGF2α regulates UAPs in both upper and lower segment cells through either direct or indirect pathways, indicating that PGF2α uniquely participates in uterine preparation for the onset of 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 | 0.000 |
| 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".