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Record W2139003615 · doi:10.1242/dmm.004069

Telomerase reverse transcriptase-dependent telomere equilibration mitigates tissue dysfunction in <i>mTert</i> heterozygotes

2009· article· en· W2139003615 on OpenAlexaff
Marie Mezníková, Natalie Erdmann, Rich Allsopp, Lea Harrington

Bibliographic record

VenueDisease Models & Mechanisms · 2009
Typearticle
Languageen
FieldMedicine
TopicTelomeres, Telomerase, and Senescence
Canadian institutionsOntario Institute for Cancer Research
FundersNational Institute on AgingWellcome TrustHoward Hughes Medical Institute
KeywordsTelomereTelomeraseTelomerase reverse transcriptaseReverse transcriptaseHeterozygote advantageBiologyMolecular biologyCell biologyGeneticsDNARNAGeneGenotype

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.213
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.250
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations19
Published2009
Admission routes1
Has abstractyes

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