Phorbol ester treatment of human myometrial cells suppresses expression of oxytocin receptor through a mechanism that does not involve activator protein-1
Bibliographic record
Abstract
Oxytocin (OT) is a potent uterine agonist. Its receptor (OTR) is a G protein-coupled receptor that is downregulated by prolonged exposure to OT. We hypothesized that activation of PKC mediated this OT-induced decrease in OTR expression. Diminished PKC activity in late pregnancy could underlie the increased expression of uterine OTR preceding labor onset. Using cell cultures of transformed human uterine myocytes, we determined the effects of PKC agonists and antagonists on the expression of OTR. We also explored the effects of overexpression of activator protein-1 (AP-1, a mediator of many PKC- and phorbol ester-induced effects) using adenoviral expression vectors for the AP-1 subunits c-Jun and c-Fos. Stimulation of PKC using the phorbol ester 12-O-tetradecanoylphorbol 13-acetate caused a rapid, significant (P < or = 0.05) increase in c-Jun and c-Fos concentrations but a significant decrease in mRNA for OTR within 6 h followed by a significant decrease in OT binding by 24 h. Adenoviral infection of the cells with expression vectors for c-Jun and c-Fos increased the AP-1 subunits but had no effect on OTR expression. Furthermore, there were no changes in c-Fos or c-Jun levels in human intrauterine tissues around the time of labor onset, as measured by Western analyses. We conclude that phorbol ester treatment decreases OTR expression, likely through a mechanism that does not involve AP-1.
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) | 0.001 | 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) | 0.003 | 0.001 |
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".