Role of circulating neurotoxins in the pathogenesis of hepatic encephalopathy: potential for improvement following their removal by liver assist devices
Bibliographic record
Abstract
Both acute and chronic liver failure result in impaired cerebral function known as hepatic encephalopathy (HE). Evidence suggests that HE is the consequence of the accumulation in brain of neurotoxic and/or neuroactive substance including ammonia, manganese, aromatic amino acids, mercaptans, phenols, short-chain fatty acids, bilirubin and a variety of neuroactive medications prescribed as sedatives to patients with liver failure. Brain ammonia concentrations may attain levels in excess of 2 mm, concentrations which are known to adversely affect both excitatory and inhibitory neurotransmission as well as brain energy metabolism. Manganese exerts toxic effects on dopaminergic neurones. Prevention and treatment of HE continues to rely heavily on the reduction of circulating ammonia either by reduction of gut production using lactulose or antibiotics or by increasing its metabolism using L-ornithine-L-aspartate. No specific therapies have so far been designed to reduce circulating concentrations of other toxins. Liver assist devices offer a potential new approach to the reduction of circulating neurotoxins generated in liver failure. In this regard, the Molecular Adsorbents Recirculating System (MARS) appears to offer distinct advantages over hepatocyte-based systems.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".