GPR101 drives growth hormone hypersecretion and gigantism in mice via constitutive activation of G <sub>s</sub> and G <sub>q/11</sub>
Bibliographic record
Abstract
Growth hormone (GH) is a key modulator of growth and GH over‐secretion can lead to gigantism. One form is X‐linked acrogigantism (X‐LAG), in which infants develop GH secreting pituitary tumors over‐expressing the orphan G‐protein coupled receptor, GPR101. The role of GPR101 in GH secretion remains obscure. We studied GPR101 signaling pathways and their effects in HEK293 and rat pituitary GH3 cell lines, human tumors and in transgenic mice with elevated somatotrope Gpr101 expression driven by the rat Ghrhr promoter ( Ghrhr Gpr101 ). We report that Gpr101 causes elevated GH/prolactin secretion in transgenic Ghrhr Gpr101 mice. We also show that GPR101 promotes GH secretion through the activation of not only G s , but also G q/11 , in a PKA and PKC‐dependent manner, respectively. Interestingly, in stark contrast with other G s ‐coupled receptors, GPR101 activation did not lead to the proliferation of somatotrope cells. These signatures of GPR101 signaling, notably PKC activation, are also present in human X‐LAG pituitary tumors with high GPR101 expression. These results underline a role for GPR101 in the regulation of somatotrope axis function.
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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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".