Chronic oral supplementation with sepiapterin prevents endothelial dysfunction and oxidative stress in small mesenteric arteries from diabetic (db/db) mice
Bibliographic record
Abstract
We previously reported that acute incubation with tetrahydrobiopterin (BH4) or sepiapterin, a cofactor for endothelial nitric oxide synthase and a stable precursor of BH4, respectively, enhanced the acetylcholine (Ach)-induced relaxation of isolated small mesenteric arteries (SMA) from diabetic (db/db) mice. In this study, we investigated the effect of chronic oral supplementation of sepiapterin (10 mg x kg-1 x day-1) to db/db mice on endothelium function, biopterin levels and lipid peroxidation in SMA. Oral dietary supplementation with sepiapterin had no effect on glucose, triglyceride, cholesterol levels and body weight. SMA from db/db mice showed enhanced vascular reactivity to phenylephrine, which was corrected with sepiapterin supplementation. Furthermore, Ach, but not sodium nitroprusside-induced relaxation, was improved with sepiapterin supplementation in db/db mice. BH4 levels and guanosine triphosphate cyclohydrolase I activity in SMA were similar in db/+ and db/db mice. Sepiapterin treatment had no effects on BH4 or guanosine triphosphate cyclohydrolase I activity. However, the level of dihydrobiopterin+biopterin was higher in SMA from db/db mice, which was corrected following sepiapterin treatment. Thiobarbituric acid reactive substance, malondialdehyde, a marker of lipid peroxidation, was higher in SMA from db/db mice, and was normalized by sepiapterin treatment. These results indicate that sepiapterin improves endothelial dysfunction in SMA from db/db mice by reducing oxidative stress. Furthermore, these results suggest that decreased biosynthesis of BH4 may not be the basis for endothelial dysfunction in SMA from db/db mice.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".