Different drug sensitivity profiles of acute myeloid and lymphoblastic leukemia and normal peripheral blood mononuclear cells in children with and without Down syndrome
Bibliographic record
Abstract
Children with Down syndrome (DS) have an increased risk for leukemia. The prognosis for DS acute myeloid leukemia (AML) is better than for non-DS AML, but the clinical outcome of DS acute lymphoblastic leukemia (ALL) is equal to that of non-DS ALL. Differences in prognosis may reflect differences in cellular drug resistance. In vitro drug resistance profiles were successfully investigated on leukemic cells from 13 patients with DS AML and 9 patients with DS ALL and were compared with reference data from 151 non-DS AML and 430 non-DS B-cell precursor (BCP) ALL. DS AML cells were significantly more sensitive to cytarabine (median, 12-fold), the anthracyclines (2-7-fold), mitoxantrone (9-fold), amsacrine (16-fold), etoposide (20-fold), 6-thioguanine (3-fold), busulfan (5-fold), vincristine (23-fold), and prednisolone (more than 1.1-fold), than non-DS AML cells. Compared with DS ALL, DS AML cells were significantly more sensitive to cytarabine only (21-fold). After short-term exposure to methotrexate, DS AML cells were 21-fold more resistant than non-DS AML cells, but no difference was observed after continuous exposure. DS ALL cells and non-DS BCP-ALL cells were equally sensitive to all drugs, including methotrexate. Normal peripheral blood mononuclear cells from DS and non-DS children without leukemia showed highly resistant drug profiles. It was concluded that the better prognosis of DS AML might, at least partially, be explained by a specific, relatively sensitive drug-resistance profile, reflecting the unique biology of this disease. (Blood. 2002;99:245-251)
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".