Polyploidy impairs human aortic endothelial cell function and is prevented by nicotinamide phosphoribosyltransferase
Bibliographic record
Abstract
Polyploid endothelial cells are found in aged and atherosclerotic arteries. However, whether increased chromosome content has an impact on endothelial cell function is unknown. We show here that human aortic endothelial cells become tetraploid as they approach replicative senescence. Furthermore, accumulation of tetraploid endothelial cells was accelerated during growth in high glucose. Interestingly, induction of polyploidy was completely prevented by modest overexpression of the NAD+ regenerating enzyme, nicotinamide phosphoribosyltransferase (Nampt). To determine the impact of polyploidy on endothelial cell function, independent of replicative senescence, we induced tetraploidy using the spindle poison, nocodazole. Global gene expression analyses of tetraploid endothelial cells revealed a dysfunctional phenotype characterized by a cell cycle arrest profile (decreased CCNE2/A2, RBL1, BUB1B; increased CDKN1A) and increased expression of genes involved in inflammation (IL32, TNFRSF21/10C, PTGS1) and extracellular matrix remodeling (COL5A1, FN1, MMP10/14). The protection from polyploidy conferred by Nampt was not associated with enhanced poly(ADP-ribose) polymerase-1 or sirtuin (SIRT) 2 activity, but with increased SIRT1 activity, which reduced cellular reactive oxygen species and the associated oxidative stress stimulus for the induction of polyploidy. We conclude that human aortic endothelial cells are prone to chromosome duplication that, in and of itself, can induce characteristics of endothelial dysfunction. Moreover, the emergence of polyploid endothelial cells during replicative aging and glucose overload can be prevented by optimizing the Nampt-SIRT1 axis.
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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".