The role of telomeres and telomerase reverse transcriptase isoforms in pluripotency induction and maintenance
Bibliographic record
Abstract
Telomeres are linear guanine-rich DNA structures at the ends of chromosomes. The length of telomeric DNA is actively regulated by a number of mechanisms in highly proliferative cells such as germ cells, cancer cells, and pluripotent stem cells. Telomeric DNA is synthesized by way of the ribonucleoprotein called telomerase containing a reverse transcriptase (TERT) subunit and RNA component (TERC). TERT is highly conserved across species and ubiquitously present in their respective pluripotent cells. Recent studies have uncovered intricate associations between telomeres and the self-renewal and differentiation properties of pluripotent stem cells. Interestingly, the past decade's work indicates that the TERT subunit also has the capacity to modulate mitochondrial function, to remodel chromatin structure, and to participate in key signaling pathways such as the Wnt/β-catenin pathway. Many of these non-canonical functions do not require TERT's catalytic activity, which hints at possible functions for the extensive number of alternatively spliced TERT isoforms that are highly expressed in pluripotent stem cells. In this review, some of the established and potential routes of pluripotency induction and maintenance are highlighted from the perspectives of telomere maintenance, known TERT isoform functions and their complex regulation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".