N-Acetylcysteine alters disease progression and increases Janus Kinase mutation frequency in a mouse model of precursor B cell acute lymphoblastic leukemia
Bibliographic record
Abstract
Abstract B cell acute lymphoblastic leukemia (B-ALL) is the most prevalent type of cancer in young children and is associated with high levels of reactive oxygen species (ROS). The antioxidant N-acetylcysteine (NAC) was tested for its ability to alter disease progression in a mouse model of B-ALL. Mb1-CreΔPB mice have deletions in genes encoding PU.1 and Spi-B in B cells and develop B-ALL at 100% incidence. Treatment of Mb1-CreΔPB mice with NAC in drinking water significantly reduced the frequency of CD19 + pre-B ALL cells infiltrating the thymus at 11 weeks of age. However, treatment with NAC did not reduce leukemia progression or increase survival by median 16 weeks of age. NAC significantly altered gene expression in leukemias in treated mice. Mice treated with NAC had increased frequencies of activating mutations in genes encoding Janus Kinases 1 and 3. In particular, frequencies of Jak3 R653H mutations were increased in mice treated with NAC compared to control drinking water. NAC opposed oxidization of PTEN protein ROS in cultured leukemia cells. These results show that NAC alters leukemia progression in this mouse model, ultimately selecting for leukemias with high Jak3 R653H mutation frequencies.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".