Deletion of Gαq/11 or Gαs Proteins in Gonadotropes Differentially Affects Gonadotropin Production and Secretion in Mice
Bibliographic record
Abstract
Gonadotropin-releasing hormone (GnRH) regulates gonadal function via its stimulatory effects on gonadotropin production by pituitary gonadotrope cells. GnRH is released from the hypothalamus in pulses and GnRH pulse frequency differentially regulates follicle-stimulating hormone (FSH) and luteinizing hormone (LH) synthesis and secretion. The GnRH receptor (GnRHR) is a G protein-coupled receptor that canonically activates Gα q/11-dependent signaling on ligand binding. However, the receptor can also couple to Gα s and in vitro data suggest that toggling between different G proteins may contribute to GnRH pulse frequency decoding. For example, as we show here, knockdown of Gα s impairs GnRH-stimulated FSH synthesis at low- but not high-pulse frequency in a model gonadotrope-derived cell line. We next used a Cre-lox conditional knockout approach to interrogate the relative roles of Gα q/11 and Gα s proteins in gonadotrope function in mice. Gonadotrope-specific Gα q/11 knockouts exhibit hypogonadotropic hypogonadism and infertility, akin to the phenotypes seen in GnRH- or GnRHR-deficient mice. In contrast, under standard conditions, gonadotrope-specific Gα s knockouts produce gonadotropins at normal levels and are fertile. However, the LH surge amplitude is blunted in Gα s knockout females and postgonadectomy increases in FSH and LH are reduced both in males and females. These data suggest that GnRH may signal principally via Gα q/11 to stimulate gonadotropin production, but that Gα s plays important roles in gonadotrope function in vivo when GnRH secretion is enhanced.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".