Ankyrin‐repeat and SOCS‐box Protein 9 (ASB9) regulate Ovarian Granulosa Cells function and MAPK signaling
Bibliographic record
Abstract
Ankyrin‐repeat and SOCS‐box Protein 9 (ASB9) was previously identified as a differentially expressed gene in ovulatory follicles post‐luteinizing hormone (LH) surge or hCG injection in ovarian granulosa cells (GC). ASB9 interactions in GC were also identified and included PAR1, TNFAIP6/TSG6, and TAOK1. However, ASB9 mechanisms of action in GC is still undefined. We investigated the role of ASB9 in GC through specific binding partners, its effects on MAPK signaling and on GC proliferation. An in vivo modelof GC from follicles at different developmental stages, small follicles (SF), dominant follicles (DF), and ovulatory follicles (OF) and an in vitro model of cultured GC along with the CRISPR/Cas9 approach to inhibit ASB9 were used. Inhibition of ASB9 in GC resulted in significant increase in PAR1 , PCNA , CCND2, and CCNE2 and significant decrease in TAOK1 , TNFAIP6 , and CASP3 expression. From i n vivo samples, PAR1 was differentially expressed in DF as compared to OF while TSG6 and TAOK1 were induced in OF. Further analyses showed an increase in GC number and a decrease in apoptosis and caspase3/7 activity following ASB9 inhibition. Western blot analyses demonstrated that ASB9 induction in OF by hCG from 12h post‐hCG through 24h was concomitant with a significant decrease in MAPK3/1 phosphorylation levels while pMAPK3/1 increased following ASB9 inhibition. These results provide strong evidence that ASB9 is a regulator of GC activity and function by modulating MAPK signaling pathway likely through specific binding partners such as PAR1, therefore controlling GC proliferation and contributing to GC differentiation into luteal 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) | 0.002 | 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".