Effect of febuxostat on biochemical parameters of hyperlipidemia induced by a high-fat diet in rabbits
Bibliographic record
Abstract
Febuxostat, a highly potent xanthine oxidase inhibitor with an antioxidant effect, inhibits elevated xanthine oxidase, leading to reduction of reactive oxygen species and oxidative stress, the main causes of vascular inflammation in hyperlipidemia. The aim of this study was to test the potential antioxidant and anti-inflammatory effects of febuxostat and (or) stopping a high-fat diet on the biochemical parameters in rabbits with hyperlipidemia induced by a high-fat diet. Male New Zealand rabbits were distributed into 3 groups: a normal control group fed standard chow for 12 weeks and 2 other groups fed a high-fat diet with 1% cholesterol for 8 weeks, and then shifted to standard chow for 4 weeks. During the last 4 weeks, one high-fat diet group received 0.5% carboxymethyl cellulose, whereas the other group was treated with febuxostat (2 mg/kg per day p.o.). Febuxostat significantly lowered low-density lipoprotein cholesterol ("bad" cholesterol) compared to the untreated group (high-fat diet group). Febuxostat also displayed a potent anti-inflammatory and antioxidant activity by decreasing serum levels of lipid peroxidation index, proinflammatory cytokines, and enhancing antioxidant enzyme activity. Stopping the hyperlipidemic diet in the high-fat diet group did not show improvement. These findings indicate the antioxidant and anti-inflammatory effects of febuxostat that may be common mechanisms of the anti-hyperlipidemic effect of this drug. Stopping a hyperlipidemic diet without treatment is not sufficient once injury has occurred.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| 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 | 0.001 | 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".