The role of protein kinase C-δ in PTH stimulation of IGF-binding protein-5 mRNA in UMR-106–01 cells
Bibliographic record
Abstract
We have investigated the role of protein kinase C (PKC) signal transduction pathways in parathyroid hormone (PTH) regulation of insulin-like growth factor-binding protein-5 (IGFBP-5) gene expression in the rat osteoblast-like cell line UMR-106-01. Involvement of the PKC pathway was determined by the findings that bisindolylmaleimide I inhibited 40% of the PTH effect, and 1 microM bovine PTH-(3-34) stimulated a 10-fold induction of IGFBP-5 mRNA. PTH-(1-34) and PTH-(3-34) (100 nM) both stimulated PKC-delta translocation from the membrane to the nuclear fraction. Rottlerin, a PKC-delta-specific inhibitor, and a dominant negative mutant of PKC-delta were both able to significantly inhibit PTH-(1-34) and PTH-(3-34) induction of IGFBP-5 mRNA, suggesting a stimulatory role for PKC-delta in the effects of PTH. Phorbol 12-myristate 13-acetate (PMA) stimulated PKC-alpha translocation from the cytosol to the membrane and inhibited approximately 50% of the PTH-(1-34), forskolin, and 8-bromoadenosine 3',5'-cyclic monophosphate-stimulated IGFBP-5 mRNA levels, suggesting that PKC-alpha negatively regulates protein kinase A (PKA)-mediated induction of IGFBP-5 mRNA. These results suggest that the induction of IGFBP-5 by PTH is both PKA and PKC dependent and PKC-delta is the primary mediator of the effects of PTH via the PKC pathway.
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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 | 0.000 | 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".