Induction of osteoblast differentiation indexes by PTHrP in MG-63 cells involves multiple signaling pathways
Bibliographic record
Abstract
Parathyroid hormone (PTH)-related peptide (PTHrP) can modulate the proliferation and differentiation of a number of cell types including osteoblasts. PTHrP can activate a G protein-coupled PTH/PTHrP receptor, which can interface with several second-messenger systems. In the current study, we have examined the signaling pathways involved in stimulated type I collagen and alkaline phosphatase expression in the human osteoblast-derived osteosarcoma cells, MG-63. By use of Northern blotting and histochemical analysis, maximum induction of these two markers of osteoblast differentiation occurred after 8 h of treatment with 100 nM PTHrP-(1-34). Chemical inhibitors of adenylate cyclase (H-89) or of protein kinase C (chelerythrine chloride) each diminished PTHrP-mediated type I collagen and alkaline phosphatase stimulation in a dose-dependent manner. These effects of PTHrP could also be blocked by inhibiting the Ras-mitogen-activated protein kinase (MAPK) pathway with a Ras farnesylation inhibitor, B1086, or with a MAPK inhibitor, PD-98059. Transient transfection of MG-63 cells with a mutant form of Galpha, which can sequester betagamma-subunits, showed significant downregulation of PTHrP-stimulated type I collagen expression, as did inhibition of phosphatidylinositol 3-kinase (PI 3-kinase) by wortmannin. Consequently, the betagamma-PI 3-kinase pathway may be involved in PTHrP stimulation of Ras. Collectively, these results demonstrate that, acting via its G protein-coupled receptor, PTHrP can induce indexes of osteoblast differentiation by utilizing multiple, perhaps parallel, signaling pathways.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".