STAT1 promotes megakaryopoiesis downstream of GATA-1 in mice
Bibliographic record
Abstract
Thrombocytosis is associated with inflammation, and certain inflammatory cytokines, including IFN-gamma, stimulate megakaryocyte and platelet production. However, the roles of IFN-gamma and its downstream effector STAT1 in megakaryocyte development are poorly understood. We previously reported that STAT1 expression was significantly downregulated in Gata1-knockdown murine megakaryocytes, which also have impaired terminal maturation. Here, we show that ectopic expression of STAT1, or its target effector IRF-1, rescued multiple defects in Gata1-deficient megakaryopoiesis in mice, inducing polyploidization and expression of a subset of platelet-expressing genes. Enforced expression of STAT1, IRF-1, or GATA-1 enhanced phosphorylation of STAT1, STAT3, and STAT5 in cultured Gata1-deficient murine megakaryocytes, with concomitant megakaryocyte maturation. In contrast, enhanced thrombopoietin signaling, conferred by enforced expression of constitutively active JAK2 or c-MPL, induced phosphorylation of STAT3 and STAT5, but not STAT1, and failed to rescue megakaryocyte maturation. Finally, megakaryocytes from Stat1(-/-) mice were defective in polyploidization. Together, these findings reveal a unique role for STAT1 in megakaryopoiesis and provide new insights into how GATA-1 regulates this process. Our studies elucidate potential mechanisms by which various inflammatory disorders can cause elevated platelet counts.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".