Double knockout of steroidogenic factor 1 (<i>NR5A1</i>) and liver receptor homolog 1 (<i>NR5A2</i>) in the mouse ovary results in infertility due to disruption of follicle development and ovulation
Bibliographic record
Abstract
Liver receptor homolog 1 (LRH-1; Nr5a2) and steroidogenic factor 1 (SF-1; Nr5a1) are two closely related orphan nuclear receptors that bind to the same genomic motif. Conditional depletion of either of these receptors in the ovary results in infertility, but through different mechanisms, with SF-1 being critical early in ovarian development and LRH-1 regulating ovulation. We conditionally depleted both LRH-1 and SF-1 from the ovary, using two different models of conditional depletion, generating two lines of double conditional knockout (dko) mice. In one, we used the Amhr2Cre (Amhr2-dko) mouse, where depletion is initiated in the prenatal ovary before the stage of germ cell nest breakdown. In the other, we employed Cyp19a1Cre (Cyp19a1-dko)-mediated depletion, which is initiated following formation of the follicular antrum. Both models were completely anovulatory and infertile, and no ovulation occurred following administration of exogenous gonadotropins. The Amhr2-dko mouse had dramatically reduced follicular populations at every stage of development, as well as disrupted extracellular matrix, characterized by dysregulation of collagen and laminin expression in reproductively mature mice, reduced expression of steroidogenic genes, dysregulated lipid metabolism, and inhibited granulosa cell proliferation. The latter resulted in a phenotype of reduced ovarian size in this model. The Cyp19al dko mouse displayed dysregulation of luteinizing hormone (LH) response and ovulatory mechanisms and increased activation of the activin/inhibin signaling axis, suggesting impaired gonadotropin responsiveness. In summary, both dko models demonstrated a phenotype of complete infertility, confirming the critical importance of both LRH-1 and SF-1 in ovarian function.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".