Structure–function relationship and biogenesis regulation of the human telomerase holoenzyme
Bibliographic record
Abstract
Telomeres are nucleoprotein structures found at the ends of linear chromosomes. Telomeric DNA shortens with each cell division, effectively restricting the proliferative capacity of human cells. Telomerase, a specialized reverse transcriptase, is responsible for de novo synthesis of telomeric DNA, and is the major physiological means by which mammalian cells extend telomere length. Telomerase activity in human soma is developmentally regulated according to cell type. Failure to tightly regulate telomerase has dire consequences: dysregulated telomerase activity is observed in more than 90% of human cancers, while haplo-insufficient expression of telomerase components underlies several inherited premature aging syndromes. Over the past decade, we have significantly improved our understanding of the structure-activity relationships between the two core telomerase components: telomerase reverse transcriptase and telomerase RNA. Genetic screening for telomerase deficiency syndromes has identified new partners in the biogenesis of telomerase and its catalytic functions. These data revealed a level of regulation complexity that is unexpected when compared with the other cellular polymerases. In this review, we summarize current knowledge on the structure-activity relationships of telomerase reverse transcriptase and telomerase RNA, and discuss how the biogenesis of telomerase provides additional regulation of its actions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".