Fine-tuning of MEK signaling is pivotal for limiting B and T cell activation
Bibliographic record
Abstract
MEK1 and MEK2, the only known activators of ERK, are attractive therapeutic candidates for both cancer and autoimmune diseases. However, how MEK signaling finely regulates immune cell activation is only partially understood. To address this question, we specifically delete Mek1 in hematopoietic cells in the Mek2 null background. Characterization of an allelic series of Mek mutants reveals the presence of distinct degrees of spontaneous B cell activation, which are inversely proportional to the levels of MEK proteins and ERK activation. While Mek1 and Mek2 null mutants have a normal lifespan, 1Mek1 and 1Mek2 mutants retaining only one functional Mek1 or Mek2 allele in hematopoietic cell lineages die from glomerulonephritis and lymphoproliferative disorders, respectively. This establishes that the fine-tuning of the ERK/MAPK pathway is critical to regulate B and T cell activation and function and that each MEK isoform plays distinct roles during lymphocyte activation and disease development.
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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 | 0.000 |
| 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".