EGF-like Growth Factors Induce COX-2–Derived PGE2 Production Through ERK1/2 in Human Granulosa Cells
Bibliographic record
Abstract
CONTEXT: Aberrant regulation of ovulation is one of the major causes of infertility. In animal models, 3 epidermal growth factor (EGF)-like growth factors, amphiregulin (AREG), betacellulin (BTC), and epiregulin (EREG), have been shown to be involved in ovulation by regulating cyclooxygenase-2 (COX-2) expression and prostaglandin E2 (PGE2) production. However, whether the same is true in humans remains largely unknown. OBJECTIVE: Our objective was to investigate the effects of AREG, BTC, and EREG on COX-2 expression and PGE2 production in human granulosa cells. DESIGN AND SETTING: SVOG cells are human granulosa cells that were obtained from women undergoing in vitro fertilization and immortalized with SV40 large T antigen. SVOG cells were used to investigate the effect of AREG, BTC, and EREG on ovulation-related functions at an academic research center. MAIN OUTCOME MEASURES: Levels of mRNA and protein were examined by quantitative RT-PCR and Western blotting, respectively. The protein levels of PGE2 were measured by ELISA. RESULTS: LH treatment upregulated AREG, BTC, EREG, and COX-2. Knockdown of EGF receptor (EGFR) attenuated LH-induced COX-2 expression and PGE2 production. Treatment with AREG, BTC, and EREG upregulated COX-2 expression and PGE2 production. The stimulatory effects of AREG, BTC, and EREG on COX-2 expression and PGE2 production were blocked by inhibition of EGFR activity and expression. AREG-, BTC-, and EREG-activated ERK1/2 signaling, but not Akt signaling, was required for AREG-, BTC-, and EREG-induced COX-2 expression and PGE2 production. CONCLUSION: AREG, BTC, and EREG induced PGE2 production by upregulating COX-2 expression through ERK1/2 signaling in human granulosa cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".