A putative protein–RNA complex regulates posttranscriptional processing of cytochrome P450 aromatase (CYP19A1) in bovine granulosa cells
Bibliographic record
Abstract
Follicle growth and granulosa cell health are dependent on the secretion of estradiol from granulosa cells. Estradiol is synthesized from androgen precursor by cytochrome P450 aromatase (CYP19A1), and in cattle CYP19A1 messenger RNA has a short half-life but a long (3.5 kb) 3'-untranslated region (3'UTR), suggesting that posttranscriptional regulation may be important for control of enzyme activity. We tested this hypothesis by inserting the CYP19A1 3'UTR and fragments thereof into a reporter vector between the end of the luciferase coding region and the polyadenylation signal. The full-length aromatase 3'UTR suppressed luciferase activity to 10% of control levels, and smaller fragments showed that this inhibitory activity lies between +926 and +1134 of the 3'UTR. Protein-RNA cross-linking experiments revealed that these 3'UTR fragments formed an RNA-protein complex of approximately 70 kDa that was present in granulosa cells but not in corpus luteum, lung, liver, kidney, pancreas, or bladder extracts. The RNA-binding activity was specific to the 3'UTR, as shown by competition experiments with unlabeled RNA, and was present only in 3'UTR constructs that inhibited luciferase activity. These data suggest that posttranscriptional regulation is an important component of the control of CYP19A1 expression and involves protein binding to a specific sequence in the 3'UTR.
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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 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".