Insulin induces steroidogenesis in canine luteal cells via PI3K-MEK-MAPK
Bibliographic record
Abstract
Glucose uptake increases in canine luteal cells under insulin treatment. We hypothesize that insulin also increases luteal cell steroidogenesis. Dogs underwent elective ovariohysterectomy from days 10-60 post ovulation and their corpora lutea (CL) and blood samples were collected. Deep RNA sequencing determined differentially expressed genes in CL; those related to insulin signaling and steroidogenesis were validated in vivo by qPCR and their respective proteins by Western blotting and immunofluorescence. Next, luteal cell cultures were stimulated with insulin with or without inhibition of MAPK14, MAP2K1 and PI3K. Studied proteins except P450 aromatase showed the same expression pattern of coding genes in vivo. The expression of HSD3B and CYP19A1 was higher in insulin-treated cells (P < 0.005). Following respective pathway blockades, the culture medium had decreased concentrations of progesterone (P4) and 17b-estradiol (E2) (P < 0.01). Our results indicate that insulin increases HSD3B and CYP19A1 expression via MAPK and PI3K, and contributes to the regulation of P4 and E2 production in canine 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 | 0.001 |
| 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".