Increased<scp>l</scp>-arginine uptake and inducible nitric oxide synthase activity in aortas of rats with heart failure
Bibliographic record
Abstract
L-Arginine crosses the cell membrane primarily through the system y(+) transporter. The aim of this study was to investigate the role of L-arginine transport in nitric oxide (NO) production in aortas of rats with heart failure induced by myocardial infarction. Tumor necrosis factor-alpha levels in aortas of rats with heart failure were six times higher than in sham rats (P < 0.01). L-Arginine uptake was increased in aortas of rats with heart failure compared with sham rats (P < 0.01). Cationic amino acid transporter-2B and inducible (i) nitric oxide synthase (NOS) expression were increased in aortas of rats with heart failure compared with sham rats (P < 0.05). Aortic strips from rats with heart failure treated with L-arginine but not D-arginine increased NO production (P < 0.05). The effect of L-arginine on NO production was blocked by L-lysine, a basic amino acid that shares the same system y(+) transporter with L-arginine, and by the NOS inhibitor N(G)-nitro-L-arginine methyl ester (L-NAME). Treatment with L-lysine and L-NAME in vivo decreased plasma nitrate and nitrite levels in rats with heart failure (P < 0.05). Our data demonstrate that NO production is dependent on iNOS activity and L-arginine uptake and suggest that L-arginine transport plays an important role in enhanced NO production in heart failure.
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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".