Insulin-like growth factor-1 (IGF-1) induces the activation/phosphorylation of Akt kinase and cAMP response element-binding protein (CREB) by activating different signaling pathways in PC12 cells
Bibliographic record
Abstract
BACKGROUND: Insulin-like growth factor-1 (IGF-1) is a polypeptide growth factor with a variety of functions in both neuronal and non-neuronal cells. IGF-1 plays anti-apoptotic and other functions by activating multiple signaling pathways including Akt kinase, a serine/threonine kinase essential for cell survival. The nuclear transcription factor cAMP response element-binding protein (CREB) may also be involved although relationships between these two proteins in IGF-1 receptor signaling and protection is not clear, especially in neuronal cells. RESULTS: IGF-1, in a concentration- and time-dependent manner, induces the activation/phosphorylation of Akt and CREB in PC12 cells by activating different signaling pathways. IGF-1 induced a sustained phosphorylation of Akt while only a transient one was seen for CREB. The phosphorylation of Akt is mediated by the PI3 kinase pathway while that of CREB is dependent on the activation of both MAPK kinase and p38 MAPK. Moreover, the stimulation of PKC attenuated the phosphorylation of Akt induced by IGF-1 while enhancing that of CREB. Survival assays with various kinase inhibitors suggested that the activation/phosphorylation of both Akt and CREB contributes to IGF-1 mediated cell survival in PC12 cells. CONCLUSION: These data suggest that IGF-1 induced the activation of Akt and CREB using distinct pathways in PC12 cells.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".