Induction of prostaglandin E2 production by leukemia inhibitory factor promotes migration of first trimester extravillous trophoblast cell line, HTR-8/SVneo
Bibliographic record
Abstract
BACKGROUND: The invasion of first trimester extravillous trophoblast (EVT) to decidua is an important event in placentation. Leukemia inhibitory factor (LIF) is an essential factor for mouse implantation, and it is reported that LIF may be involved in human first trimester EVT invasion. Prostaglandin E2 (PGE2) is also known as a critical factor for first trimester EVT invasion. In this study, we investigated the role of LIF in PGE2 production and EVT invasion using a human first trimester EVT cell line, HTR-8/SVneo. METHODS AND RESULTS: Co-stimulation with LIF and IL-1beta induced higher amounts of PGE2 production and further migration of HTR-8/SVneo cells compared with that by stimulation with LIF or IL-1beta alone. Enhanced PGE2 production was most probably due to the enhanced expression of cyclooxygenase-2 (COX-2) and microsomal PGE synthase-1 (mPGES-1). PGE2 produced by HTR-8/SVneo cells promoted the migration of HTR-8/SVneo cells. A COX-2 inhibitor suppressed PGE2 production and the migration of HTR-8/SVneo cells. Agonists to PGE2 receptors, EP1, EP2 and EP4, promoted the migration of HTR-8/SVneo cells. Moreover, stimulation with LIF up-regulated EP1, EP2 and EP4 expression in HTR-8/SVneo cells. CONCLUSIONS: It is suggested that LIF participates in placentation through EVT invasion by up-regulating PGE2 production and PGE2 receptor expression in first trimester EVT.
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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) | 0.001 | 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".