Bibliographic record
Abstract
Non-coding tandem repeat DNA sequences have high rates of mutation that facilitate the measurement of induced mutation in small sample sizes. It has been suggested that these loci may be useful biomarkers for heritable genetic mutation induced by exposure to genotoxic agents. Significant induction of mutation is quantifiable in the germline of mice exposed to mutagens. The primary focus of this work has been on exposure to radiation. The data suggest that meiosis or DNA replication/repair may be required for induction of mutation in the germline at tandem repeats. Mutations arise via indirect mechanisms rather than by direct damage to the repeat locus itself, therefore reflecting genomic instability rather than targeted DNA damage. These markers have also been used to measure induced germline mutations in animals exposed to ambient levels of urban air pollution. The mutagenicity is associated with particulate matter in the air but the exact chemical nature of the mutagens is unknown. Lack of knowledge of the relationship between ESTR instability and gene mutation, and lack of understanding of the mechanisms resulting in instability prevent inference on the health-related implications of induced tandem repeat mutation. We have developed single-molecule PCR approaches to study ESTR instability in vitro. This method circumvents the requirement of sub-cloning and allows for many more individual ESTR alleles to be examined. These types of laboratory-based experiments will be crucial in clarifying the types of chemicals that can generate tandem repeat instability and thereby provide insight into the mechanisms of action and the putative mutagens found in complex environmental matrices.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".