Cytoprotective potential of tiron and methyl palmitate against acetaminophen-induced acute liver injury
Bibliographic record
Abstract
Acute liver injury is a debilitating disorder associated with loss of synthetic and detoxifying functions of the liver. This investigation was designed to assess cytoprotective efficacy of daily oral tiron (300 mg/kg) and daily oral methyl palmitate (300 mg/kg) against acetaminophen-induced acute liver injury. Rats were orally pretreated with either tiron or methyl palmitate at doses (300 mg/kg) for 7 days prior to oral acetaminophen (3 g/kg). Biochemical assay of markers of hepatotoxicity indices and oxidative stress was undertaken. Expression of inflammatory cytokine IL-6 was also evaluated. Histopathological examination of liver specimens was carried out as well. Both methyl palmitate and tiron significantly reversed the acetaminophen-induced elevation of biochemical markers (ALT, AST, and ALP) with restoration of SOD levels. Serum albumin levels and GSH liver contents increased, but in a nonsignificant manner. Moreover, methyl palmitate and tiron significantly decreased the level of serum LDH and serum IL-6 levels. Histopathology revealed that tiron markedly reduced the extent of acetaminophen-induced necrosis and methyl palmitate moderately decreased the necrosis in liver tissue. Methyl palmitate (300 mg/kg) and tiron (300 mg/kg) demonstrated promising hepatoprotective effects against acetaminophen-induced acute liver injury via modulation of inflammatory response and alleviation of the oxidative stress, allowing the preservation of hepatic functions.
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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 | 0.000 | 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 | 0.000 |
| 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".