Extra-chromosomal telomeric DNA in cells from Atm-/- mice and patients with ataxia-telangiectasia
Bibliographic record
Abstract
Ataxia-telangiectasia (AT) is an autosomally recessive human genetic disease with pleiotropic defects such as neurological degeneration, immunodeficiency, chromosomal instability, cancer susceptibility and premature aging. Cells derived from AT patients and ataxia-telangiectasia mutated (ATM)-deficient mice show slow growth in culture and premature senescence. ATM, which belongs to the PI3 kinase family along with DNA-PK, plays a major role in signaling the p53 response to DNA strand breaks. Telomere maintenance is perturbed in yeast strains lacking genes homologous to ATM and cells from patients with AT have short telomeres. We examined the length of individual telomeres in cells from ATM(-/-) mice by fluorescence in situ hybridization. Telomeres were extensively shortened in multiple tissues of ATM(-/-) mice. More than the expected number of telomere signals was observed in interphase nuclei of ATM(-/-) mouse fibroblasts. Signals corresponding to 5-25 kb of telomeric DNA that were not associated with chromosomes were also noticed in ATM(-/-) metaphase spreads. Extrachromosomal telomeric DNA was also detected in fibroblasts from AT patients and may represent fragmented telomeres or by-products of defective replication of telomeric DNA. These results suggest a role of ATM in telomere maintenance and replication, which may contribute to the poor growth of ATM(-/-) cells and increased tumor incidence in both AT patients and ATM(-/-) mice.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".