TRIB Pseudokinases Regulation and Function in Bovine Granulosa Cells
Bibliographic record
Abstract
TRIB members (TRIB1, TRIB2 and TRIB3) represent atypical members of the serine/threonine kinase superfamily and are involved in multiple biological processes such as cell proliferation and differentiation. TRIB roles in GC are not fully investigated. We hypothesized that TRIB members play crucial roles in regulating GC activity and may activate separate signaling pathways. TRIB1 and TRIB3 are induced in GC of ovulatory follicles (OF) following hCG injection as compared to dominant follicles (DF) whereas TRIB2 is suppressed by hCG in OF. Protein analyses of cultured primary GC showed that luteinizing hormone (LH) treatment inhibited TRIB2 and induced TRIB3, while follicle-stimulating hormone (FSH) treatment increased TRIB2 and TRIB3 expression but at different times. These results demonstrate a different regulation of TRIB members during follicular development and in response to gonadotropins. TRIB3 inhibition via CRISPR/Cas9 showed a positive effect on AKT signaling pathway while showing negative effects on P38 MAPK signaling. Overall, TRIBs may play crucial roles in regulating GC function and activity and may activate separate signaling pathways, which impact follicular development, ovulation and luteinization.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".