The expression of the nuclear receptors NR5A1 and NR5A2 and transcription factor GATA6 correlates with steroidogenic gene expression in the bovine corpus luteum
Why this work is in the frame
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Bibliographic record
Abstract
The corpus luteum (CL) is the major site of progesterone (P4) production during the luteal phase of the estrous cycle in cattle. To better understand the molecular mechanisms underlying P4 production, we compared the mRNA and protein expression profiles of key components of the steroidogenic pathway (StAR, CYP11A, and 3beta-HSD) during the bovine CL luteal phase with that of several transcription factors (NR5A1, NR5A2, GATA4, GATA6) known for their roles in the control of steroidogenic gene expression. In the bovine CL, StAR, CYP11A, and 3beta-HSD mRNA and protein levels remained constant at the mid and late luteal phases but markedly declined at the regressed luteal stage. NR5A1 and NR5A2 exhibited a similar pattern with a significant decrease in expression at the regressed luteal stage. Both GATA4 and GATA6 mRNA and proteins could be detected in bovine CL; GATA6 levels, however, were generally higher. Although GATA4 expression did not change during the luteal phase, GATA6 showed a marked decrease at the regressed luteal stage, like NR5A1, NR5A2, and the other steroidogenic markers. Thus, we suggest that NR5A1, NR5A2, and GATA6, but not GATA4, contribute to the transcriptional regulation of steroidogenic gene expression, and hence P4 production, in the bovine CL. Furthermore, we have demonstrated the association of NR5A1 and NR5A2 with the bovine StAR promoter in the mid-luteal CL using chromatin immunoprecipitation, suggesting that these factors have definitive roles in the regulation of StAR gene transcription in vivo.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it