The Regulation of MAPKs in Y1 Mouse Adrenocortical Tumor Cells
Bibliographic record
Abstract
The regulation of the MAPKs, Erk(1) and Erk(2), and the MAPK kinase, Mek, were examined in the Y1 mouse adrenocortical tumor cell line and in the protein kinase A-defective mutant, Kin-8. ACTH and basic fibroblast growth factor each increased Mek phosphorylation and stimulated Mek activity in both cell lines and also activated the Erks at concentrations that paralleled their effects on Mek. The specific Mek inhibitor, PD98059, blocked the activation of the Erks by ACTH and basic fibroblast growth factor, indicating that Mek is the upstream activator of Erk. PD98059 did not block the phosphorylation of Mek, as might have been expected from previous studies; instead PD98059 inhibited the activity of the activated enzyme. In ACTH-stimulated, mutant Kin-8 cells, PD98059 paradoxically increased the amount of phosphorylated Mek, while preventing the activation of Erk. These results are interpreted as reflecting the loss of a protein kinase A-mediated inhibitory influence on Mek phosphorylation and activation.
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) | 0.000 | 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 | 0.000 |
| 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".