Fucoidan reduces inflammatory response in a rat model of hepatic ischemia–reperfusion injury
Bibliographic record
Abstract
Ischemia-reperfusion (I/R) injury after a liver transplant is a major cause of severe complications that lead to graft dysfunction. Fucoidan, a complex of sulfated polysaccharides derived from marine brown algae, demonstrated antiapoptotic as well as potential anti-inflammatory properties in previous studies. Fucoidan has also shown protective effects on I/R-injured kidney and heart. However, whether fucoidan can attenuate hepatic I/R injury has not been examined. To clarify the role of fucoidan in hepatic I/R injury, Sprague-Dawley rats were subjected to sham operation or ischemia followed by reperfusion with treatment of saline or fucoidan (50, 100, or 200 mg·(kg body mass)(-1)·d(-1)). The fucoidan-treated group showed decreased levels of alanine aminotransferase and aspartate aminotransferase compared with the control group. Myeloperoxidase and malondialdehyde activities and mRNA levels of CD11b in the fucoidan-treated group were significantly decreased. Hepatocellular swelling/necrosis, sinusoidal/vascular congestion, and inflammatory cell infiltration were also attenuated in the fucoidan group. The expression of TNF-α, IL-6, IL-1β, CXCL-10, VCAM-1, and ICAM-1 were markedly decreased in the samples from the fucoidan-treated group. Fucoidan largely prevented activation of the inflammatory signaling pathway, compared with the control group. In summary, fucoidan can protect the liver from I/R injury through suppressing activation of the inflammatory signaling pathway, as well as the expression of inflammatory mediators, and inflammatory cell infiltration.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".