gp130-Mediated Signaling Is Necessary for Normal Osteoblastic Function in Vivo and in Vitro
Bibliographic record
Abstract
Previous studies have shown that mice missing gp130, the common receptor subunit for many cytokines, die at or before birth with multiple skeletal abnormalities. Furthermore, interactions between PTH and gp130 signaling have suggested that gp130 signaling might influence calcium homeostasis. We, therefore, examined the function of osteoblasts, osteoclasts, and calcium homeostasis in gp130(-/-) mice, both in vivo and in vitro. Osteoblasts from these mice exhibit widespread abnormalities, including decreased alkaline phosphatase mRNA and protein, both in vivo and in osteoblast cultures. Although osteoclast number is increased in gp130(-/-) fetuses, these osteoclasts exhibit abnormalities in the resorptive organelle and the ruffled border, and the mice are mildly hypocalcemic. Although the hypocalcemia is associated with secondary hyperparathyroidism, the increase in PTH does not explain the increase in osteoclast number because removal of the PTH gene in gp130(-/-) fetuses does not importantly change osteoclast number. Calvarial bone resorption in response to PTH is defective, as is the ability of osteoblastic cells from gp130(-/-) mice to stimulate osteoclastogenesis from normal precursors in vitro or to increase receptor activator of nuclear factor-kappa B ligand mRNA levels after exposure to PTH. These studies demonstrate the importance of gp130 signaling for osteoblast function and calcium homeostasis.
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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 | 0.000 |
| 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".