The effects of a comparatively higher dose of 1000 mg/kg/d of oral L- or D-arginine on the L-arginine metabolic pathways in male Sprague-Dawley rats
Bibliographic record
Abstract
Oral L-arginine supplements are popular mainly for their nitric oxide mediated vasodilation, but their physiological impact is not fully known. L-arginine is a substrate of several enzymes including arginase, nitric oxide synthase, arginine decarboxylase, and arginine: glycine amidinotransferase (AGAT). We have published a study on the physiological impact of oral L- and D-arginine at 500 mg/kg/day for 4 wks in male Sprague-Dawley rats. We investigated the effects of oral L-arginine and D-arginine at a higher dose of 1000 mg/kg/d for a longer treatment duration of 16 wks in 9-week-old male Sprague-Dawley rats. We measured the expression and activity of L-arginine metabolizing enzymes, and levels of their metabolites in the plasma and various organs. L-arginine did not affect the levels of L-arginine and L-lysine in the plasma and various organs. L-arginine decreased arginase protein expression in the upper small intestine, and arginase activity in the plasma. It also decreased AGAT protein expression in the liver, and creatinine levels in the urine. L-arginine altered arginine decarboxylase protein expression in the upper small intestine and liver, with increased total polyamines plasma levels. Endothelial nitric oxide synthase protein was increased with D-arginine, the presumed metabolically inert isomer, but not L-arginine. In conclusion, oral L-arginine and D-arginine at a higher dose and longer treatment duration significantly altered various enzymes and metabolites in the arginine metabolic pathways, which differed from alterations produced by a lower dose shorter duration treatment published earlier. Further studies with differing doses and duration would allow for a better understanding of oral L-arginine uses, and evidence based safe and effective dose range and duration.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".