Enrichment of Sca1+ hematopoietic progenitors in polycythemic mice inhibits leukemogenesis
Bibliographic record
Abstract
Polycythemia vera (PV) is a myeloproliferative disorder characterized by a pronounced increase in the number of erythroid cells. However, despite this aberrant proliferation, the incidence of erythroleukemia is paradoxically rare in PV patients. In this study, we show that the progression of Friend virus-induced erythroleukemia is delayed in a mouse model of primary familial congenital polycythemia in which the wild-type Epo-receptor (EpoR) gene is replaced with a truncated human EPOR gene. Herein, we show that these mice exhibit enrichment of Sca1(+)/cKit(-) progenitors and several mature immune cells, such as dendritic cells and macrophages. In cotransplantation experiments, Sca1(+)/cKit(-) progenitors inhibit the tumorigenicity of Sca1(-)/cKit(+) erythroleukemic cells. A cell line established from Sca1(+)/cKit(-) progenitors is also capable of inhibiting leukemic proliferation in culture and in mice. This phenomenon of leukemic inhibition, also detected in the serum of PV patients, is partially attributed to increased nitric oxide secretion. In addition, the administration of erythropoietin into leukemic mice induces a polycythemia-like state associated with the expansion of Sca1(+)/cKit(-) progenitors and derivative immune cells, thereby inhibiting leukemia progression. This study indicates that a combination therapy incorporating the enrichment of Sca1(+)/cKit(-) progenitors may serve as a novel approach for the treatment of 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) | 0.001 | 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) | 0.001 | 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".