Hepatoprotective effects of early pentoxifylline administration on hepatic injury induced by concanavalin A in rat
Bibliographic record
Abstract
Tumor necrosis factor alpha (TNF-α) plays an important role in the pathogensis of hepatitis C virus (HCV) infection induced liver injury. This study aimed to evaluate the effects of TNF-α inhibition with pentoxifylline (PTX) on concanavalin A (Con A)-induced hepatic injury in rats. The rats were distributed among 3 groups: (i) control group (1 mL saline·week(-1) by intravenous injection (i.v.)); (ii) Con A treatment group (20 mg Con A·(kg body mass)(-1)·week(-1), i.v.), and (iii) rats treated with Con A and with PTX (200 mg PTX·(kg body mass)(-1)·day(-1), per oral) group. Blood samples and livers were collected at the end of weeks 1, 2, 4, and 8 of Con A treatment. Portal pressure (PP) was measured at the end of week 8. The administration of PTX was found to confer significant protection against the injurious effects of Con A on the liver, by reducing serum levels of aspartate aminotransferase, alanine aminotransferase, hepatic TNF-α, and malondialdehyde. Histopathological examination revealed that treatment with PTX significantly suppressed early inflammation, reduced alpha smooth muscle actin, and the apoptosis of hepatocytes induced by Con A. Moreover, PTX significantly (P < 0.05) reduced PP, and quantitative analyses of the area of fibrosis induced by treatment with Con A showed a significant reduction at the end of week 8. We conclude that rats treated with PTX revealed a more or less normal hepatocyte architecture as well as marked improvement in fibrosis and PP.
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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) | 0.000 | 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 | 0.001 |
| 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".