The effects of N-acetylcysteine on the levels of glutathione, serum TNFα, and tissue malondialdehyde in sepsis
Bibliographic record
Abstract
This study was designed to determine the effects of N -acetylcysteine (NAC) as an antioxidant agent on the free oxygen radicals and their plasma levels. In this study, 40 Sprague–Dawley rats were randomly divided into three groups as sham ( n = 10), sepsis ( n = 10), and sepsis + NAC (20 mg/kg/24 hours) ( n = 10). An experimental sepsis model was performed by a cecal ligation and perforation (CLP). NAC was administered at 0, 8 and 16 hours after CLP. The blood samples were taken at 24 hours to determine the levels of serum TNFα and erythrocyte glutathione (GSH), and renal and liver tissue malondialdehyde (MDA). The serum TNFα levels were significantly decreased in group 3 compared with group 2 ( P < 0.05). The erythrocyte GSH levels significantly increased in group 3 compared with group 2 ( P < 0.05). In group 3, the liver MDA levels were decreased compared with group 2, but not statistically significant ( P > 0.05) In group 3, the renal MDA levels were significantly decreased compared with group 2 ( P < 0.05). The lung tissue PMNL levels significantly decreased in group 3 compared with group 2 ( P < 0.05). In an experimental sepsis model, with the administration of NAC as an antioxidant agent at lower doses, many meaningful positive effects were detected on the levels of erythrocyte GSH, serum TNFα, respiration function, and renal tissue MDA. In spite of the low dose, NAC therapies decrease the organ function abnormalities; these effects were not reflected in the histopathological investigations. These findings suggest that NAC could be a possible therapeutic agent for sepsis and its mortality. However, further studies are needed to elucidate the effects of these drugs at higher doses.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".