Noncanonical Role of Telomerase in Regulation of Microvascular Redox Environment With Implications for Coronary Artery Disease
Bibliographic record
Abstract
Abstract Telomerase reverse transcriptase (TERT) (catalytic subunit of telomerase) is linked to the development of coronary artery disease (CAD); however, whether the role of nuclear vs. mitchondrial actions of TERT is involved is not determined. Dominant-negative TERT splice variants contribute to decreased mitochondrial integrity and promote elevated reactive oxygen species production. We hypothesize that a decrease in mitochondrial TERT would increase mtDNA damage, promoting a pro-oxidative redox environment. The goal of this study is to define whether mitochondrial TERT is sufficient to maintain nitric oxide as the underlying mechanism of flow-mediated dilation by preserving mtDNA integrity.Immunoblots and quantitative polymerase chain reaction were used to show elevated levels of splice variants α- and β-deletion TERT tissue from subjects with and without CAD. Genetic, pharmacological, and molecular tools were used to manipulate TERT localization. Isolated vessel preparations and fluorescence-based quantification of mtH2O2 and NO showed that reduction of TERT in the nucleus increased flow induced NO and decreased mtH2O2 levels, while prevention of mitochondrial import of TERT augmented pathological effects. Further elevated mtDNA damage was observed in tissue from subjects with CAD and initiation of mtDNA repair mechanisms was sufficient to restore NO-mediated dilation in vessels from patients with CAD. The work presented is the first evidence that catalytically active mitochondrial TERT, independent of its nuclear functions, plays a critical physiological role in preserving NO-mediated vasodilation and the balance of mitochondrial to nuclear TERT is fundamentally altered in states of human disease that are driven by increased expression of dominant negative splice variants.
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 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".