Increased severity of alcoholic liver injury in female rats: role of oxidative stress, endotoxin, and chemokines
Bibliographic record
Abstract
Alcoholic liver injury is more severe and rapidly developing in women than men. To evaluate the reason(s) for these gender-related differences, we determined whether pathogenic mechanisms important in alcoholic liver injury in male rats were further upregulated in female rats. Male and age-matched female rats (7/group) were fed ethanol and a diet containing fish oil for 4 wk by intragastric infusion. Dextrose isocalorically replaced ethanol in control rats. We analyzed liver histopathology, lipid peroxidation, cytochrome P-450 (CYP)2E1 activity, nonheme iron, endotoxin, nuclear factor-kappa B (NF-kappa B) activation, and mRNA levels of cyclooxygenase-1 (COX-1) and COX-2, tumor necrosis factor-alpha (TNF-alpha), monocyte chemotactic protein-1 (MCP-1), and macrophage inflammatory protein-2 (MIP-2). Alcohol-induced liver injury was more severe in female vs. male rats. Female rats had higher endotoxin, lipid peroxidation, and nonheme iron levels and increased NF-kappa B activation and upregulation of the chemokines MCP-1 and MIP-2. CYP2E1 activity and TNF-alpha and COX-2 levels were similar in male and female rats. Remarkably, female rats fed fish oil and dextrose also showed necrosis and inflammation. Our findings in ethanol-fed rats suggest that increased endotoxemia and lipid peroxidation in females stimulate NF-kappa B activation and chemokine production, enhancing liver injury. TNF-alpha and COX-2 upregulation are probably important in causing liver injury but do not explain gender-related differences.
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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 | 0.001 | 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) | 0.004 | 0.001 |
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".