Arginine as a Significant Regulator of Supersaturation in Calcium Oxalate Lithiasis: the Physiological Evidence
Bibliographic record
Abstract
Background: At present, the possible effect of arginine as a natural regulator of calcium oxalate (CaOX) supersaturation and crystallization in human urine has been analyzed. Methods: Two types of experiments have been discussed: clinical laboratory analysis on the urine excretion of arginine (Arg) in patients with CaOX lithiasis and detailed measurements of the kinetics of the dissolution of CaOX calculi in artificial urine, containing various concentrations of Arg. Results: A detailed analysis showed that 80% of stone formers (SFs) eliminated pathological values: 30% of patients had lower plasma levels compared to controls and about 50% of SFs showed higher concentration. Urine concentrations in these two groups were not reported. Conclusions: The in vitro analytical measurements demonstrate even a possibility to dissolve CaOX stones in human urine, in which increased concentration of Arg has been established. Discussions have arisen to use increased concentration of Arg in urine both as a solubilizator of CaOX stones in humans and on the purpose of a prolonged metaphylactic treatment. World J Nephrol Urol. 2015;4(1):173-177 doi: http://dx.doi.org/10.14740/wjnu199w
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".