Myeloid-specific inactivation of p15Ink4b results in monocytosis and predisposition to myeloid leukemia
Bibliographic record
Abstract
Inactivation of p15INK4b, an inhibitor of cyclin-dependent kinases, through DNA methylation is one of the most common epigenetic abnormalities in myeloid leukemia. Although this suggests a key role for this protein in myeloid disease suppression, experimental evidence to support this has not been reported. To address whether this event is critical for premalignant myeloid disorders and leukemia development, mice were generated that have loss of p15Ink4b specifically in myeloid cells. The p15Ink4b(fl/fl)-LysMcre mice develop nonreactive monocytosis in the peripheral blood accompanied by increased numbers of myeloid and monocytic cells in the bone marrow resembling the myeloproliferative form of chronic myelomonocytic leukemia. Spontaneous progression from chronic disease to acute leukemia was not observed. Nevertheless, MOL4070LTR retrovirus integrations provided cooperative genetic mutations resulting in a high frequency of myeloid leukemia in knockout mice. Two common retrovirus insertion sites near c-myb and Sox4 genes were identified, and their transcript up-regulated in leukemia, suggesting a collaborative role of their protein products with p15Ink4b-deficiency in promoting malignant disease. This new animal model demonstrates experimentally that p15Ink4b is a tumor suppressor for myeloid leukemia, and its loss may play an active role in the establishment of preleukemic conditions.
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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) | 0.003 | 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".