Mek1 and Mek2 Functional Redundancy in Erythropoiesis
Bibliographic record
Abstract
Several studies have established the crucial role of the extracellular signal–regulated kinase (ERK)/mitogen-activated protein kinase pathway in hematopoietic cell proliferation and differentiation. MEK1 and MEK2 phosphorylate and activate ERK1 and ERK2. However, whether MEK1 and MEK2 differentially regulate these processes is unknown. To define the function of Mek genes in the activation of the ERK pathway during hematopoiesis, we generated a mutant mouse line carrying a hematopoietic-specific deletion of the Mek1 gene function in a Mek2 null background. Inactivation of both Mek1 and Mek2 genes resulted in death shortly after birth with a severe anemia revealing the essential role of the ERK pathway in erythropoiesis. Mek1 and Mek2 functional ablation also affected lymphopoiesis and myelopoiesis. In contrast, mice that retained one functional Mek1 (1Mek1) or Mek2 (1Mek2) allele in hematopoietic cells were viable and fertile. 1Mek1 and 1Mek2 mutants showed mild signs of anemia and splenomegaly, but the half-life of their red blood cells and the response to erythropoietic stress were not altered, suggesting a certain level of Mek redundancy for sustaining functional erythropoiesis. However, subtle differences in multipotent progenitor distribution in the bone marrow were observed in 1Mek1 mice, suggesting that the two Mek genes might differentially regulate early hematopoiesis.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".