Notch affects the prodifferentiating effect of retinoic acid and <scp>PMA</scp> on leukemic cells
Bibliographic record
Abstract
Notch proteins determine cell fate decisions in the development of diverse tissues. Notch has been initially found in T-ALL but its role has been also studied in myelopoiesis and myeloid leukemias. Studies in different model systems have led to a widespread controversy as to whether Notch promotes or blocks myeloid differentiation. In this work, we evaluated the influence of Notch activation on leukemic cell differentiation along the monocytic and myelocytic pathway induced by phorbol 12-myristate 13-acetate (PMA) or all-trans retinoic acid (ATRA). We observed that differentiation of the human myeloblastic cell line HL-60 can be retarded or blocked by Delta/Notch interaction. ATRA induces complete remission in patients with acute promyelocytic leukemia, but it cannot completely eliminate the leukemic clone and to be effective it should be combined with chemotherapy. Our findings suggest that Notch signaling may contribute to the incomplete elimination of the leukemic cells after PMA or ATRA treatment and the blockage of Notch pathway may be beneficial in the treatment of myeloid leukemia. © 2014 International Society for Advancement of Cytometry.
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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) | 0.002 | 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".