L-Ornithine L-Aspartate for the Treatment of Sarcopenia in Chronic Liver Disease: The Taming of a Vicious Cycle
Bibliographic record
Abstract
Sarcopenia is a common complication of cirrhosis with a negative impact on posttransplant outcome, health-related quality of life (HRQOL), and patient survival. Studies in experimental animals and in patients demonstrate that ammonia is directly implicated in the pathogenesis of sarcopenia in cirrhosis via mechanisms involving increased expression of myostatin and of autophagy markers such as LC3 lipidation and p62 leading to muscle dysmetabolism and sarcopenia. Paradoxically, skeletal muscle replaces liver as the primary ammonia-detoxifying site as a result of the modification of genes coding for key proteins implicated in ammonia-lowering pathways in cirrhosis. Thus, a vicious cycle occurs whereby hyperammonemia causes severe muscle damage and sarcopenia that, in turn, limits the capacity of muscle to remove excess blood-borne ammonia and the cycle continues. Randomized clinical trials and meta-analyses confirm that L-ornithine L-aspartate (LOLA) is an effective ammonia-lowering agent currently employed for the treatment of hepatic encephalopathy (HE) that stimulates both urea synthesis by residual hepatocytes and muscle glutamine synthesis together with putative hepatoprotective actions. Treatment of cirrhotic patients with LOLA limits ammonia-induced sarcopenia by improving muscle protein synthesis and function. It is conceivable that the antisarcopenic action of LOLA contributes to its efficacy for the treatment of HE in cirrhosis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| 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) | 0.003 | 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".