Elevated mRNA expression of PGF2α receptor splice variant 2(FP-V2) in human decidua is associated with incomplete mifepristone-misoprostol induced early medical abortion by regulation of interleukin-8
Bibliographic record
Abstract
OBJECTIVE: The combination of mifepristone and misoprostol is an established method for the induction of early abortion, but 15% of women still experience the unpleasant side effect of incomplete medical abortion. The purpose of this study was to determine whether prostaglandin (PG) F2α receptor (FP) and its two isoforms (FP-V1 and FP-V2) in human decidua are associated incomplete abortion. METHODS: Forty women who underwent medical abortion were recruited. Among them, there were 20 cases of incomplete abortion. The other 20 cases of complete abortion were used as controls. The expression levels of FP, FPV1 and FP-V2 in the decidua between of the two groups was detected by quantitative real-time polymerase chain reaction (PCR). Additionally, FP-V2 was knocked down using specific small interfering RNAs (siRNAs) in the primary cultures of decidual cells. The expression levels of cytokines in FP-V2 knockdown primary decidual cells and control decidual cells were detected by quantitative real-time PCR and enzyme-linked immunosorbent assay (ELISA). RESULTS: The FP and FP-V2 mRNA expression in the incomplete group was significantly higher than that in the complete group (p < 0.05). IL-8 was up-regulated by FP-V2 knockdown in primary-cultured decidual cells (p < 0.05). CONCLUSIONS: These results suggested that the elevated expression of FP-V2 in human decidua is significantly associated with incomplete mifepristone-misoprostol-induced early medical abortion and that IL-8 could be lined to this process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".