Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Stem cells, one of the progenitors of cancer, exist predominately in a quiescent state. Thus, understanding the mechanisms of DNA repair and mutagenesis in such arrested cells may help unravel the complex process of tumorigenesis. Two major nucleotide excision repair (NER) pathways are known to remove bulky physical or chemical lesions from DNA. Transcription-coupled repair (TCR) acts solely on the transcribed strand of expressed genes, while global genomic repair (GGR) is responsible for the ubiquitous repair of the genome. Indirectly, it has been shown that while TCR functions in quiescent cells GGR does not. To explicitly elucidate this phenomenon, we adapted a quantitative PCR (QPCR) assay to study UV-damage repair via TCR and GGR in quiescent and proliferating cells. We present evidence that repair of untranscribed silent regions of the genome and repair of the non-transcribed strand of active genes proceeds by two discrete mechanisms in quiescent cells; rather than by GGR, which was believed to encompass both. Thus, our findings suggest the existence of an alternate NER pathway in quiescent cells. The proposed subcategories of NER are as follows: (i) TCR, responsible for maintenance of transcribed strands; (ii) GGR, responsible for ubiquitous genome repair; and (iii) non-transcribed strand repair (NTSR), predominantly responsible for the repair of the NTS in arrested cells. In quiescent cells, it is evident that TCR and NTSR function and GGR are arrested. As a consequence, mutation accumulation at temporally silent genes and incomplete or imperfect repair of transcribed genes, in quiescent stem cells, may provide a source of cancer causing mutations.
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.
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 it