Bone marrow endothelial cell-derived interleukin-4 contributes to thrombocytopenia in acute myeloid leukemia
Bibliographic record
Abstract
Normal hematopoiesis can be disrupted by the leukemic bone marrow microenvironment, which leads to cytopenia-associated symptoms including anemia, hemorrhage and infection. Thrombocytopenia is a major and sometimes fatal complication in patients with acute leukemia. However, the mechanisms underlying defective thrombopoiesis in leukemia have not been fully elucidated. In the steady state, platelets are continuously produced by megakaryocytes. Using an MLL-AF9-induced acute myeloid leukemia mouse model, we demonstrated a preserved number and proportion of megakaryocyte-primed hematopoietic stem cell subsets, but weakened megakaryocytic differentiation via both canonical and non-canonical routes. This primarily accounted for the dramatic reduction of megakaryocytic progenitors observed in acute myeloid leukemia bone marrow and a severe disruption of the maturation of megakaryocytes. Additionally, we discovered overproduction of interleukin-4 from bone marrow endothelial cells in acute myeloid leukemia and observed inhibitory effects of interleukin-4 throughout the process of megakaryopoiesis in vivo. Furthermore, we observed that inhibition of interleukin-4 in combination with induction chemotherapy not only promoted recovery of platelet counts, but also prolonged the duration of remission in our acute myeloid leukemia mouse model. Our study elucidates a new link between interleukin-4 signaling and defective megakaryopoiesis in acute myeloid leukemia bone marrow, thereby offering a potential therapeutic target in acute myeloid leukemia.
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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".