Deferiprone increases endothelial nitric oxide synthase phosphorylation and nitric oxide production
Bibliographic record
Abstract
Iron chelation can improve endothelial function. However, effect on endothelial function of deferiprone has not been reported. We hypothesized deferiprone could promote nitric oxide (NO) production in endothelial cells. We studied effects of deferiprone on blood nitrite and blood pressure after single oral dose (25 mg/kg) in healthy subjects and hemoglobin E/β-thalassemia patients. Further, effects of deferiprone on NO production and endothelial NO synthase (eNOS) phosphorylation in primary human pulmonary artery endothelial cells (HPAEC) were investigated in vitro. Blood nitrite levels were higher in patients with deferiprone therapy than those without deferiprone (P = 0.023, n = 16 each). Deferiprone increased nitrite in plasma and whole blood of healthy subjects (P = 0.002 and 0.044) and thalassemia patients (P = 0.003 and 0.046) at time 180 min (n = 20 each). Asymptomatic reduction in diastolic blood pressure (P = 0.005) and increase in heart rate (P = 0.009) were observed in healthy subjects, but not in thalassemia patients. In HPAEC, deferiprone increased cellular nitrite and phospho-eNOS (Ser1177) (P = 0.012 and 0.035, n = 6) without alteration in total eNOS protein and mRNA. We conclude that deferiprone can induce NO production by enhancing eNOS phosphorylation in endothelial cells.
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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".