Hepatoprotection by L-Ornithine L-Aspartate in Non-Alcoholic Fatty Liver Disease
Bibliographic record
Abstract
BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is the leading chronic hepatic condition worldwide and new approaches to management and treatment are limited. SUMMARY: L-ornithine L-aspartate (LOLA) has hepatoprotective properties in patients with fatty liver of diverse etiology and results of a multicenter randomized clinical trial reveal that 12 weeks treatment with oral LOLA (6-9 g/d) results in a dose-related reduction in activities of liver enzymes and triglycerides together with significant improvements of liver/spleen CT ratios. A preliminary report described improvements of hepatic microcirculation in patients with non-alcoholic steatohepatitis (NASH) following treatment with LOLA. Mechanisms responsible for the beneficial effects of LOLA in NAFLD/NASH involve, in addition to its established ammonia-lowering effect, metabolic transformations of the LOLA-constituent amino acids L-ornithine and L-aspartate into L-glutamine, L-arginine, and glutathione. These metabolites have well-established actions implicated in the prevention of lipid peroxidation, improvement of hepatic microcirculation in addition to anti-inflammatory, and anti-oxidant properties. Key Messages: (1) LOLA is effective for the treatment of key indices in NAFLD/NASH. (2) Mechanisms other than LOLA's ammonia-lowering action have been postulated. (3) Further assessments in the clinical setting are now required.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".