The interleukin-6 trans-signaling promotes progesterone production in human granulosa-lutein cells
Bibliographic record
Abstract
As a critical paracrine regulator of multiple reproductive functions, the cytokine interleukin-6 (IL-6) is expressed in human granulosa cells and can be detected in follicular fluid. At present, the functional role of IL-6 in the regulation of ovarian steroidogenesis is controversial. Moreover, the detailed molecular mechanisms by which IL-6 regulates the production of progesterone in human granulosa cells remain to be elucidated. In the present study, we used primary and immortalized human granulosa-lutein (hGL) cells to investigate the effects of IL-6 on progesterone synthesis and the underlying molecular mechanisms. We found that IL-6 trans-signaling by the combined addition of IL-6 and soluble IL-6 receptor (sIL-6Rα)-induced steroidogenic acute regulatory expression and progesterone production in hGL cells. Additionally, IL-6/sIL-6Rα activated the phosphorylation of Janus activated kinase 2 (JAK2) and signal transducer and activator of transcription 3 (STAT3), and the cellular effects were abolished by AG490 (JAK2 inhibitor), C188-9 (STAT3 inhibitor), or siRNA-mediated knockdown of STAT3. IL-6 trans-signaling-induced activation of JAK2/STAT3 also upregulated the expression of suppressor of cytokine signaling 3, which, in turn, negatively regulated the JAK2/STAT3 pathway by suppressing STAT3 activation and its downstream effects. Our findings provide insight into the molecular mechanisms by which IL-6 trans-signaling modulates steroidogenesis in hGL cells.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".