The Hippo Pathway Effectors YAP and TAZ Regulate LH Release by Pituitary Gonadotrope Cells in Mice
Bibliographic record
Abstract
The Hippo transcriptional coactivators YAP and TAZ exert critical roles in morphogenesis, organ size determination and tumorigenesis in many tissues. Although Hippo kinase cascade activity was recently reported in the anterior pituitary gland in mice, the role of the Hippo effectors in regulating gonadotropin production remains unknown. The objective of this study was therefore to characterize the roles of YAP and TAZ in gonadotropin synthesis and secretion. Using a conditional gene targeting approach (cKO), we found that gonadotrope-specific inactivation of Yap and Taz resulted in increased circulating levels of follicle-stimulating hormone (FSH) and luteinizing hormone (LH) in adult male mice, along with increased testosterone levels and testis weight. Female cKO mice had increased circulating LH (but not FSH) levels, which were associated with a hyperfertility phenotype characterized by higher ovulation rates and larger litter sizes. Unexpectedly, the loss of YAP/TAZ did not appear to affect the expression of gonadotropin subunit genes, yet both basal and GnRH-induced LH secretion were increased in cultured pituitary cells from cKO mice. Likewise, pharmacologic inhibition of YAP binding to the TEAD family of transcription factors increased both basal and GnRH-induced LH secretion in LβT2 gonadotrope-like cells in vitro without affecting Lhb expression. Conversely, mRNA levels of ChgA and SgII, which encode key secretory granule cargo proteins, were decreased following pharmacologic inhibition of YAP/TAZ, suggesting a mechanism whereby YAP/TAZ regulate the LH secretion machinery in gonadotrope cells. Together, these findings represent the first evidence that Hippo signaling may play a role in regulating pituitary LH secretion.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".