Discovery of why acute lymphoblastic leukaemia cells are killed by asparaginase: Adventures of a young post-doctoral student, Bertha K Madras
Bibliographic record
Abstract
A surprising finding was made by JG Kidd (1909-1991) that guinea pig serum could make tumours disappear in mice. A later finding made by JD Broome (1939-) showed that asparaginase could suppress or kill tumour cells. However, the major mystery was why were only tumour cells but not normal cells affected by the asparaginase? The biology underlying this mechanism was unravelled by a young post-doctoral student, Bertha K Madras (1942-) who hypothesized that cells with low asparagine synthetase are those that die following treatment with asparaginase. To test her theory, Madras developed an assay for asparagine synthetase. The hypothesis was supported by the results that cells with normal asparagine synthetase were protected, while cells with low levels of this enzyme were killed by asparaginase. The findings provide a clinical guide for the use of asparaginase in acute lymphoblastic leukaemia in children and adults.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.008 |
| 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".