Further characterization and validation of <i>gpt</i> delta transgenic mice for quantifying somatic mutations in vivo
Bibliographic record
Abstract
The utility of any mutation assay depends on its characteristics, which are best discovered using model mutagens. To this end, we report further on the characteristics of the lambda-based gpt delta transgenic assay first described by Nohmi et al. ([1996]: Environ Mol Mutagen 28:465-470). Our studies show that the gpt transgene responds similarly to other transgenic loci, specifically lacZ and cII, after treatment with acute doses of N-ethyl-N-nitrosourea (ENU). Because genetic neutrality is an important factor in the design of treatment protocols for mutagenicity testing, as well as for valid comparisons between different tissues and treatments, a time-course study was conducted. The results indicate that the gpt transgene, like cII and lacZ, is genetically neutral in vivo. The sensitivities of the loci are also equivalent, as evidenced by spontaneous mutant frequency data and dose- response curves after acute treatment with 50, 150, or 250 mg/kg ENU. The results are interesting in light of transgenic target size and location and of host genetic background differences. Based on these studies, protocols developed for other transgenic assays should be suitable for the gpt delta. Additionally, a comparison of the gpt and an endogenous locus, Dlb-1, within the small intestine of chronically treated animals (94 microg/mL ENU in drinking water daily) shows differential accumulation of mutations at the loci during chronic exposure. The results further support the existence of preferential repair at endogenous, expressed genes relative to transgenes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".