CHILDHOOD ACUTE LYMPHOBLASTIC LEUKEMIA (ALL) PRESENTING WITH SEVERE OSTEOLYSIS: A Model to Study Leukemia-Bone Interactions and Potential Targeted Therapeutics
Bibliographic record
Abstract
Interference with the molecular mechanisms that generate tumor supportive niches in the bone microenvironment is a rational approach to inhibit the growth of hematological malignancies. However, the advancement of knowledge in this area has been slowed down by the lack of in vitro models to facilitate the screening of potential candidate agents. The rare cases of acute lymphoblastic leukemia (ALL) in children presenting with extensive bone involvement may represent an exaggerated form of some aspects of the normal tumor-bone interactions. Thus, these cases can provide insight into processes that are otherwise challenging to uncover. The authors describe the case of a 6-year-old child who presented with severe osteopenia that resolved at the time of leukemic remission. Compared to control sera, serum taken at disease presentation contained increased levels of a group of osteolytic cytokines and was effective in activating preosteoclast cells in culture. Based on these findings, the authors describe an experimental model to identify agents that would interfere with leukemia mediated osteolytic process.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".