Telomeres, A Busy Platform for Cell Signaling
Bibliographic record
Abstract
Telomeres are the terminal structures at the ends of linear chromosomes that represent a solution to the end replication problem. Specific binding of the six-protein subunit complex shelterin to telomeric, repetitive TTAGGG DNA sequences contributes to the stable architecture and maintenance of telomeres. Proteins involved in the DNA damage response are also localized at telomeres, and play a role in the surveillance and maintenance of telomere integrity. The enzyme responsible for telomere extension is telomerase, a ribonucleoprotein with reverse transcriptase activity. In the absence of telomerase, telomeres shorten to a length threshold that triggers the DNA damage response and replicative senescence. Here, we will summarize the latest findings concerning vertebrate telomere structure and epigenetics, and we present data regarding the impact of short telomeres upon cell signaling. In particular, in murine embryonic stem cells lacking telomerase, we found that distribution of cytosolic/nuclear β-catenin, a key component of the Wnt signaling pathway, changes when telomeres become critically short. We discuss implications and future perspectives of the effect of epigenetic modifications and/or conformational changes of telomeres on cell metabolism and signaling networks. Such an analysis may unveil potential therapeutic targets for pathologies like cancer, where the integrity of telomeres is altered.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".