TGF-β1 Up-Regulates Connective Tissue Growth Factor Expression in Human Granulosa Cells through Smad and ERK1/2 Signaling Pathways
Bibliographic record
Abstract
Connective tissue growth factor (CTGF), which is also called CCN2, is a secreted matricellular protein. CTGF regulates various important cellular functions by interacting with multiple molecules in the microenvironment. In the ovary, CTGF is mainly expressed in granulosa cells and involved in the regulation of follicular development, ovulation and luteinization. TGF-β1 has been shown to up-regulate CTGF expression in rat and hen granulosa cells. However, the underlying molecular mechanisms of this up-regulation remain undefined. More importantly, whether the stimulatory effect of TGF-β1 on CTGF expression can be observed in human granulosa cells remains unknown. In the present study, our results demonstrated that TGF-β1 treatment up-regulates CTGF expression in both immortalized human granulosa cells and primary human granulosa cells. Using a siRNA-mediated knockdown approach and a pharmacological inhibitor, we demonstrated that the inhibition of Smad2, Smad3 or ERK1/2 attenuates the TGF-β1-induced up-regulation of CTGF. This study provides important insights into the molecular mechanisms that mediate TGF-β1-up-regulated CTGF expression in human granulosa 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 | 0.000 |
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".