The antioxidant and anti-inflammatory activities of caffeine effectively attenuate nonalcoholic steatohepatitis and thioacetamide-induced hepatic injury in male rats
Bibliographic record
Abstract
The antioxidant effect of caffeine, associated with its ability to upregulate the nuclear factor-E2-related factor-2 (Nrf2)-signaling pathway, was explored as a possible mechanism for the attenuation of liver damage. Nonalcoholic steatohepatitis (NASH) was induced in rats by the administration of a high-fat, high-sucrose, high-cholesterol diet (HFSCD) for 15 weeks. Liver damage was induced in rats by intraperitoneal administration of thioacetamide (TAA) for six weeks. Caffeine was administered orally at a daily dose of 50 mg/kg body weight during the period of NASH induction to evaluate its ability to prevent disease development. Meanwhile, rats received TAA for three weeks, after which 50 mg/kg caffeine was administered daily for three weeks with TAA to evaluate its capacity to interfere with the progression of hepatic injury. HFSCD administration induced hepatic steatosis, decreased Nrf2 levels, increased oxidative stress, induced the activation of nuclear factor-κB (NF-κB), and elevated proinflammatory cytokine levels, leading to hepatic damage. TAA administration produced similar effects, excluding steatosis. Caffeine increased Nrf2 levels; attenuated oxidative stress markers, including malondialdehyde and 4-hydroxynonenal; restored normal, reduced glutathione levels; and reduced NF-κB activation, inflammatory cytokine levels, and damage. Our findings suggest that caffeine may be useful in the treatment of human liver diseases.
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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 | 0.001 | 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".