Simultaneous measurement of benzo[<i>a</i>]pyrene‐induced<i>Pig‐a</i>and<i>lacZ</i>mutations, micronuclei and dna adducts in muta<sup>TM</sup>mouse
Bibliographic record
Abstract
In this study we compared the response of the Pig-a gene mutation assay to that of the lacZ transgenic rodent mutation assay, and demonstrated that multiple endpoints can be measured in a 28-day repeat dose study. Muta™Mouse were dosed daily for 28 days with benzo[a]pyrene (BaP; 0, 25, 50 and 75 mg/kg body weight/day) by oral gavage. Micronucleus (MN) frequency was determined in reticulocytes (RETs) 48 hr following the last dose. 72 h following the last dose, mice were euthanized, and tissues (glandular stomach, small intestine, bone marrow and liver) were collected for lacZ mutation and DNA adduct analysis, and blood was evaluated for Pig-a mutants. BaP-derived DNA adducts were detected in all tissues examined and significant dose-dependent increases in mutant Pig-a phenotypes (i.e., RET(CD24-) and RBC (CD24-)) and lacZ mutants were observed. We estimate that mutagenic efficiency (i.e., rate of conversion of adducts into mutations) was much lower for Pig-a compared to lacZ, and speculate that this difference is likely explained by differences in repair capacity between the gene targets, and differences in the cell populations sampled for Pig-a versus lacZ. The BaP doubling doses for both gene targets, however, were comparable, suggesting that similar mechanisms are involved in the accumulation of gene mutations. Significant dose-related increases in % MN were also observed; however, the doubling dose was considerably higher for this endpoint. The similarity in dose response kinetics of Pig-a and lacZ provides further evidence for the mutational origin of glycosylphosphatidylinositol (GPI)-anchor deficiencies detected in the Pig-a assay.
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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) | 0.000 | 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 | 0.001 | 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".