Methylglyoxal modulates endothelial nitric oxide synthase-associated functions in EA.hy926 endothelial cells
Bibliographic record
Abstract
BACKGROUND: Increased levels of the sugar metabolite methylglyoxal (MG) in vivo were shown to participate in the pathophysiology of vascular complications in diabetes. Alterations of endothelial nitric oxide synthase (eNOS) activity by hypophosphorylation of the enzyme and enhanced monomerization are found in the diabetic milieu, and the regulation of this still remains undefined. Using various pharmacological approaches, we elucidate putative mechanisms by which MG modulates eNOS-associated functions of MG-stimulated superoxide O₂•⁻ production, phosphorylation status and eNOS uncoupling in EA.hy926 human endothelial cells. METHODS: In cultured EA.hy926 endothelial cells, the effects of MG treatment, tetrahydrobiopterin (BH4; 100 μM) and sepiapterin (20 μM) supplementation, NOS inhibition by N(G)-nitro-L-arginine methyl ester (L-NAME; 50 μM), and inhibition of peroxynitrite (ONOO⁻) formation (300 μM Tempol plus 50 μM L-NAME) on eNOS dimer/monomer ratios, Ser-1177 eNOS phosphorylation and 3-nitrotyrosine (3NT) abundance were quantified using immunoblotting. O₂•⁻-dependent fluorescence was determined using a commercially available kit and tissue biopterin levels were measured by fluorometric HPLC analysis. RESULTS: In EA.hy926 cells, MG treatment significantly enhanced O₂•⁻ generation and 3NT expression and reduced Ser-1177 eNOS phosphorylation, eNOS dimer/monomer ratio and cellular biopterin levels indicative of eNOS uncoupling. These effects were significantly mitigated by administration of BH4, sepiapterin and suppression of ONOO⁻ formation. L-NAME treatment significantly blunted eNOS-derived O₂•⁻ generation but did not modify eNOS phosphorylation or monomerization. CONCLUSION: MG triggers eNOS uncoupling and hypophosphorylation in EA.hy926 endothelial cells associated with O₂•⁻ generation and biopterin depletion. The observed effects of the glycolysis metabolite MG presumably account, at least in part, for endothelial dysfunction in diabetes.
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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".