Vascular endothelial function is improved by oral glycine treatment in aged rats
Bibliographic record
Abstract
Glycine has been used to reduce oxidative stress and proinflammatory mediators in some metabolic disorders; however, its effect on the vasculature has been poorly studied. The aim of this work was to explore the effect of glycine on endothelial dysfunction in aged rats. Aortic rings with intact or denuded endothelium were obtained from untreated or glycine-treated male Sprague-Dawley rats at 5 and 15 months of age. Concentration-response curves to phenylephrine (PHE) were obtained from aortic rings incubated with N(G)-nitro-l-arginine methyl ester (l-NAME), superoxide dismutase (SOD), indomethacin, SC-560, and NS-398. Aortic mRNA expression of endothelial nitric oxide synthase (eNOS), NADPH oxidase 4 (NOX-4), cyclooxygenase 1 (COX-1), cyclooxygenase 2 (COX-2), tumour necrosis factor (TNF)-α, and interleukin-1 β was measured by real time RT-PCR. The endothelial modulation of the contraction by PHE was decreased in aortic rings from aged rats. Glycine treatment improved this modulator effect and increased relaxation to acetylcholine. Glycine augmented the sensitivity for PHE in the presence of l-NAME and SOD. It also reduced the contraction by incubation with indomethacin, SC-560, and NS-398. Glycine increased the mRNA expression of eNOS and decreased the expression of COX-2 and TNF-α. Glycine improved the endothelium function in aged rats possibly by enhancing eNOS expression and reducing the role of superoxide anion and contractile prostanoids that increase the nitric oxide bioavailability.
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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 | 0.000 | 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 | 0.001 |
| 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".