Genes for prostaglandin synthesis, transport and inactivation are differentially expressed in human uterine tissues, and the prostaglandin F synthase AKR1B1 is induced in myometrial cells by inflammatory cytokines
Bibliographic record
Abstract
Prostaglandins (PGs) are important factors in the physiology of human parturition and the control of uterine contractility. We have characterized the expression of 15 genes from all stages of the PG pathway in human pregnant and non-pregnant (NP) myometrium and in other uterine tissues at delivery, and the results show patterns indicative of different capacities for PG synthesis and catabolism in each tissue. In placenta, the PG synthase expression profile favours production of PGD₂, PGE₂ and PGF₂, with high levels of PG transporters and catabolic PG dehydrogenase suggesting rapid PG turnover. Choriodecidua is primed for PGE₂, PGF₂ and PGD₂ production and high PG turnover, whereas amnion expresses genes for PGE₂ synthesis with low levels of PG transporters and dehydrogenase. In umbilical cord, PGI₂ synthase is highly expressed. In pregnant myometrium, PGI₂, PGD₂ and PGF₂ synthases are highly expressed, whereas PG dehydrogenase is underexpressed. Myometrium from women with spontaneous or induced labour had higher expression of the PGH₂ synthase PTGS2 than tissue from women not-in-labour. Myometrium from NP women had lower levels of PG synthases and higher levels of PG dehydrogenase than pregnant myometrium. Discriminant function analysis showed that expression of selected genes in myometrium could distinguish groups of women with different modes of labour from each other and from NP women. In cultured myometrial cells, there was a dose-dependent stimulatory effect of interleukin 1β and tumour necrosis factor α on PTGS2, PTGES and AKR1B1 (PGF synthase) expression.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".