In Vitro (CTG)·(CAG) Expansions and Deletions by Human Cell Extracts
Bibliographic record
Abstract
The mechanism of disease-associated (CTG)*(CAG) expansion may involve DNA replication slippage, replication direction, Okazaki fragment processing, recombination, or repair. A length-dependent bias for expansions is observed in humans affected by a trinucleotide repeat-associated disease. We developed an assay to test the effect of replication direction on (CTG)*(CAG) instabilities incurred during in vitro (SV40) DNA replication mediated by human cell extracts. This system recapitulates the bias for expansions observed in humans. Replication by HeLa cell extracts generated expansions and deletions that depended upon repeat tract length and the direction of replication. Templates with 79 repeats yielded predominantly expansions (CAG as lagging strand template) or predominantly deletions (CTG as lagging strand template). Templates containing 17 repeats were stable. Thus, replication direction determined the type of mutation. These results provide new insights into the orientation of replication effect upon repeat stability. This system will be useful in determining the contribution of specific human proteins to (CTG)*(CAG) expansions.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".