Proliferation is necessary for both repair and mutation in transgenic mouse cells
Bibliographic record
Abstract
Proliferating cells are often presumed to be more mutable than quiescent cells because they have less time to repair DNA damage before DNA replication. Direct tests of this hypothesis have been confounded by the need for cell division before a mutation can be detected. We have avoided this problem by showing that the Big Blue mouse cell line permits the dynamic quantification of both lesions and mutations in the complete absence of cell division. These cells carry the bacterial lacI gene in a lambda shuttle vector. Mutant plaques recovered by in vitro packaging of the mouse DNA can arise from mutations sustained either in mouse cells or in the bacteria. The proportion of mutant phage contained within a mutant plaque can distinguish these two types of mutation. Mutations formed in mouse cells yield >90% mutant phage because both DNA strands are mutant. On the other hand, mutations formed in the bacteria from adducted DNA yield </=50% mutant phage, because one of the DNA strands is wild type. Immediately after exposure to a test mutagen, ethylnitrosourea, all induced mutations were formed in the bacteria, but after approximately one cell division, the reverse was true and all mutations arose in the mouse cells. Only one-fifth as many mutations were recovered from quiescent cells and all arose in the bacteria, showing that the mouse cells made no mutations in the absence of proliferation. Surprisingly, the mouse cells did not repair any of the premutagenic damage during 4 days of quiescence. When these quiescent cells were induced to proliferate, however, both repair and mutation fixation ensued.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".