Labour is associated with decreased expression of the PGF2 receptor (PTGFR) and a novel PTGFR splice variant in human myometrium but not decidua
Bibliographic record
Abstract
The prostaglandin F(2α) receptor (PTGFR) is believed to play a role in the process of parturition. The main support for this comes from animal studies; however, in humans, the evidence is less clear. The gene coding for PTGFR may be subject to alternative splicing to generate alternate variants with different signalling pathways. We have determined regional (upper versus lower segment) and labour-associated expression of PTGFR mRNA and a recently identified splice variant of PTGFR in human myometrium and decidua. We also examined the effect of the inflammatory cytokine interleukin-1β (IL-1β) on PTGFR mRNA expression in a model of cultured human myometrial smooth muscle cells. We identified a PTGFR transcript variant 2 (PTGFR-v2) generated by alternate splicing in human myometrium and decidua. The PTGFR-v2 contains an additional 71 base pair exon, which results in a truncated protein at 297 amino acids compared with the PTGFR transcript variant 1 (PTGFR-v1) at 359 amino acids. In contrast to our hypothesis, we demonstrate that PTGFR-v1 and PTGFR-v2 mRNA expression is not significantly higher in upper segment compared with lower segment paired samples. We also show a labour-associated decrease in PTGFR-v1 and PTGFR-v2 mRNA expression in lower segment myometrial samples. IL-1β-stimulated mRNA expression of both PTGFR variants in a distinct time-dependent manner in myometrial cell cultures. We suggest that the role of the PTGFR in the human uterus requires further validation prior to pursuing it as a target for the treatment of preterm labour. In addition, the presence of distinct variants suggests further levels of gene regulation within the pregnant uterus.
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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".