Tetraploidy impairs human aortic endothelial cell (HAEC) function and is prevented by nicotinamide phosphoribosyltransferase (Nampt)
Bibliographic record
Abstract
Senescent EC are found in atherosclerotic arteries and contribute to impaired vasodilation and inflammation. Polyploid EC are also found in atherosclerosis, but the consequences of this change are unclear. In HAEC, we found that tetraploidy precedes replicative senescence, is worsened during growth in high glucose, and is delayed by the NAD + regenerating enzyme, Nampt. However, the impact of tetraploidy on EC function, independent of senescence, is unknown. Likewise, the effect of Nampt on EC genomic stability during replicative aging and glucose overload is unknown. We induced senescence‐independent tetraploidy by incubating HAEC with nocodazole for 48 h. After a 24 h recovery, these cells were 70% tetraploid, with no change in senescence‐associated β‐galactosidase activity. Growth rate and eNOS protein were decreased (‐38%, ‐23%) and ICAM‐1 protein was increased (19%). The effect of Nampt on tetraploidy associated with replicative senescence and glucose overload was assessed in HAEC expressing eGFP or eGFP‐Nampt and grown in basal (5 mM) or high (30 mM) glucose to the end of their lifespan. Nampt completely prevented aging‐ and glucose overload‐induced tetraploidy. We conclude that tetraploidy can independently impair HAEC function and that the emergence of tetraploidy during replicative aging and glucose overload can be prevented by enhancing NAD + salvage. Research support: HSFO T5675, CIHR FRN11715.
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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 | 0.000 | 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".