Telomerase reverse transcriptase-dependent telomere equilibration mitigates tissue dysfunction in <i>mTert</i> heterozygotes
Bibliographic record
Abstract
Autosomal dominant mutations in telomere-associated factors elicit a disease known as dyskeratosis congenita (DKC), and patients suffer proliferative abnormalities associated with telomere erosion. Mice that are heterozygous for telomerase genes (Tert or Terc, hereafter referred to as mTert and mTerc) are useful models of telomerase haploinsufficiency, but do not strictly mimic DKC. In strains with long telomeres (>60 kbp), animals that are heterozygous for mTert undergo telomere erosion for nine generations and remain phenotypically normal. In an mTerc heterozygous strain with short telomeres (<15 kbp), early mortality arises after five to six generations, but dyskeratosis occurs only upon the further loss of mPot1b. We show that prolonged mTert heterozygosity (for greater than ten generations) did not elicit disease, even upon heterozygote interbreeding, and that telomeres reset to wild-type lengths. This lengthening did not occur in nullizygotes, and short telomeres inherited from mTert null parents were rescued only in heterozygous progeny. In the bone marrow, nullizygotes remained competent for radioprotection for three generations. Thus, gradual telomere erosion in the presence of telomerase may enable subsequent telomere extension, similar to that described in budding yeast. We speculate whether such adaptation occurs in normal human cells (or whether it could be induced in DKC-derived cells), and whether it might mitigate the impact of telomerase inhibition upon stem cells during cancer therapy.
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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 | 0.000 | 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) | 0.002 | 0.000 |
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".