Expression of the prostaglandin F synthase AKR1B1 and the prostaglandin transporter SLCO2A1 in human fetal membranes in relation to spontaneous term and preterm labor
Bibliographic record
Abstract
BACKGROUND: Human labor is a complex series of cellular and molecular events that occur at the materno-fetal and uterine levels. Many hypotheses have been proposed for the initiation of human labor, one hypothesis suggests that maturation of the fetus releases a signal in the amniotic fluid that will be transmitted to myometrium via the fetal membranes and initiate uterine contractions. There is strong evidence that prostaglandins (PGs) play a central role in initiation and progression of human labor. OBJECTIVES: In this study we intended to investigate the expression of prostaglandin F synthase and the prostaglandin transporter in the human fetal membranes and to explore the relationship between cytokines and PGs in the mechanism of human labor. METHODS: We used fetal membranes obtained before labor at term and after spontaneous labor at term or preterm to identify the changes in prostaglandin F synthase (AKR1B1) and human prostaglandin transporter (SLCO2A1) proteins in relation to parturition. Using fetal membranes explants we tested the effect of cytokines (interleukin-1 and tumor necrosis factor alpha) on PG production and the concomitant changes in cyclooxygenase-2 (PTGS2), AKR1B1 and SLCO2A1 expression. RESULTS: Expression of PTGS2 and AKR1B1 was upregulated in the fetal membranes in association with term labor while SLCO2A1 was downregulated with advancing gestation and during term labor. Before labor, IL-1 increased the expression of PTGS2, however during labor TNF upregulated PTGS2 and AKR1B1 proteins. CONCLUSIONS: The prostaglandin F synthase AKR1B1 is upregulated while prostaglandin transporter is downregulated during term labor. The amnion is more responsive than choriodecidua to stimulation with pro-inflammatory cytokines. The mechanisms of term and preterm labor are different.
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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 | 0.001 |
| 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".