Bibliographic record
Abstract
Central nervous system (CNS) complications of liver failure include hepatic encephalopathy (HE) and brain edema. Recent research driven primarily by studies in experimental animal models suggests that inflammation, acting alone or in concert with ammonia, plays a key role in the pathogenesis of these complications. It is well established that systemic inflammation worsens encephalopathy and brain edema and its complications in acute liver failure (ALF) and more recently, evidence for the presence of neuroinflammation (inflammatory processes in the brain per se) has been accumulating. Evidence in favor of neuroinflammatory mechanisms includes the finding of microglial activation in brain (microglia are the immunomodulator cells of the brain) together with increased brain accumulation of proinflammatory cytokines such as TNF-α, IL-1β, and IL-6. Although the precise nature of the signaling mechanisms between the failing liver and the brain leading to neuroinflammation is unknown, mechanisms involving blood–brain cytokine transfer and brain lactate have been proposed. Neuroinflammatory responses in liver failure result in upregulation of translocator protein (TLP), a mitochondrial membrane protein that is particularly concentrated in microglia. Positron emission tomography studies using the TLP ligand C-PK11195 in cirrhotic patients with mild HE reveal increased signals consistent with microglial activation and neuroinflammation. It has been proposed that existing therapies for HE including lactulose, rifaximin, albumen dialysis, and probiotics have the potential to lower both circulating ammonia and proinflammatory cytokines. Moreover, mild hypothermia and N -acetylcysteine have similar joint actions. Treatment of experimental animals with liver failure due to liver ischemia or toxic liver injury reveals that minocycline, an agent with potent inhibitory actions on microglial activation or the TNF-α receptor antagonist etanercept, leads to slowing of progression of encephalopathy and brain edema in ALF. Translation of these findings to the clinic has the potential to provide novel strategies for the management and treatment of the CNS complications of liver failure in the future.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".