Thromboxane Inhibitors Attenuate Inflammatory and Fibrotic Changes in Rat Liver Despite Continued Ethanol Administrations
Bibliographic record
Abstract
BACKGROUND: Thromboxane levels are increased in rats fed ethanol (EtOH), whereas thromboxane inhibitors reduce alcoholic liver injury. The aim of this study is to determine whether thromboxane inhibitors could attenuate the already established alcoholic liver injury. METHODS: Rats were fed EtOH and liquid diet for 6 weeks by intragastric infusion to induce liver injury after which EtOH was continued for 2 more weeks, and the rats were treated with either a thromboxane synthase inhibitor (TXSI) or a thromboxane receptor antagonist (TXRA). Liver pathology, lipid peroxidation, nuclear factor-kappa-B (NF-κB) activity, tumor necrosis factor-α (TNF-α), cyclooxygenase-2 (COX-2), and transforming growth factor-beta1 (TGF-β(1) ) were evaluated. RESULTS: Administration of fish oil and EtOH caused fatty liver, necrosis, inflammation and fibrosis accompanied by increased in lipid peroxidation, NF-κB activity, and expression of TNF-α, COX-2, and TGF-β(1) . Treatment with the thromboxane inhibitors ameliorated a certain level of the pathological and biochemical abnormalities. In particular, TXSI in addition to reducing necrosis, inflammation and fibrosis also decrease the severity of fatty liver. CONCLUSIONS: Thromboxane inhibitors attenuated the alcoholic liver injury, inflammation and fibrotic changes despite continued EtOH administration. Inhibition of the production of thromboxane by thromboxane inhibitor and receptor antagonists may be a useful treatment strategy in clinical alcoholic liver disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.001 |
| 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 teacher head, 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".