Extracellular‐regulated kinase—mitogen‐activated protein kinase cascade: Unsolved issues
Bibliographic record
Abstract
This review point out several aspects regarding the mitogen-activated protein kinase (MAPK)/extracellular-regulated kinase (Erk) network, which are still pending issues in the understanding how this pathway integrate information to drive cell fates. Focusing on the role of Erk during cell cycle, it has to be underlined that Erk downstream effectors, which are required for mitosis progression and contribute to aneuploidy during tumorigenesis, remain to be determined. In addition to the identity of the terminal enzymes or effectors of Erk, it has to be stressed that the dynamic nature of the Erk signal is itself a key factor in cell phenotype decisions. Development of biophotonics strategies for monitoring the Erk network at the spatiotemporal level in living cells, as well as computational and hypothesis-driven approaches, are called to unravel the principles by which signaling networks create biochemical and biological specificities. Finally, Erk dynamics might also be impacted by other post-translational modification than phosphorylation, such as O-GlcNAcylation.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.005 |
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".