<i>In medio stat virtus</i> : unanticipated consequences of telomere dysequilibrium
Bibliographic record
Abstract
The integrity of chromosome ends, or telomeres, depends on myriad processes that must balance the need to compact and protect the telomeric, G-rich DNA from detection as a double-stranded DNA break, and yet still permit access to enzymes that process, replicate and maintain a sufficient reserve of telomeric DNA. When unable to maintain this equilibrium, erosion of telomeres leads to perturbations at or near the telomeres themselves, including loss of binding by the telomere protective complex, shelterin, and alterations in transcription and post-translational modifications of histones. Although the catastrophic consequences of full telomere de-protection are well described, recent evidence points to other, less obvious perturbations that arise when telomere length equilibrium is altered. For example, critically short telomeres also perturb DNA methylation and histone post-translational modifications at distal sites throughout the genome. In murine stem cells for example, this dysregulated chromatin leads to inappropriate suppression of pluripotency regulator factors such as Nanog . This review summarizes these recent findings, with an emphasis on how these genome-wide, telomere-induced perturbations can have profound consequences on cell function and fate. This article is part of the theme issue ‘Understanding diversity in telomere dynamics’.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".