Integrated <i>In Vivo</i> Genotoxicity Assessment of Procarbazine Hydrochloride Demonstrates Induction of <i>Pig‐a</i> and <i>LacZ</i> Mutations, and Micronuclei, in MutaMouse Hematopoietic Cells
Bibliographic record
Abstract
Procarbazine hydrochloride (PCH) is a DNA‐reactive hematopoietic carcinogen with potent and well‐characterized clastogenic activity. However, there is a paucity of in vivo mutagenesis data for PCH, and in vitro assays often fail to detect the genotoxic effects of PCH due to the complexity of its metabolic activation. We comprehensively evaluated the in vivo genotoxicity of PCH on hematopoietic cells of male MutaMouse transgenic rodents using a study design that facilitated assessments of micronuclei and Pig‐a mutation in circulating erythrocytes, and lacZ mutant frequencies in bone marrow. Mice were orally exposed to PCH (0, 6.25, 12.5, and 25 mg/kg/day) for 28 consecutive days. Blood samples collected 2 days after cessation of treatment exhibited significant dose‐related induction of micronuclei in both immature and mature erythrocytes. Bone marrow and blood collected 3 and 70 days after cessation of treatment also showed significantly elevated mutant frequencies in both the lacZ and Pig‐a assays even at the lowest dose tested. PCH‐induced lacZ and Pig‐a (immature and mature erythrocytes) mutant frequencies were highly correlated, with R2 values ≥0.956, with the exception of lacZ vs. Pig‐a mutants in mature erythrocytes at the 70‐day time point (R2 = 0.902). These results show that PCH is genotoxic in vivo and demonstrate that the complex metabolism and resulting genotoxicity of PCH is best evaluated in intact animal models. Our results further support the concept that multiple biomarkers of genotoxicity, especially hematopoietic cell genotoxicity, can be readily combined into one study provided that adequate attention is given to manifestation times. Environ. Mol. Mutagen. 60:505–512, 2019. © 2018 Her Majesty the Queen in Right of Canada
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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) | 0.001 | 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".