Celecoxib decreases fatty acid synthase expression via down-regulation of c-Jun N-terminal kinase-1.
Bibliographic record
Abstract
Nonsteroidal anti-inflammatory drugs (NSAIDs) are inhibitors of cyclooxygenase (COX). Our previous observations that celecoxib, a COX-2-specific inhibitor, not only inhibits rat mammary carcinogenesis, but also decreases fat deposition in rats fed a high-fat diet, prompted us to determine whether celecoxib affects lipid metabolism. At 57 days of age, two groups of 10 female Sprague Dawley rats were pair-fed a high-fat diet with or without 1500 ppm celecoxib for 15 weeks. Compared with controls, celecoxib-treated rats had 44.4% less hepatic triglycerides and 22.6% less intra-abdominal adipose tissue mass. In the liver and adipose tissue of several genes involved in fat metabolism and mobilization that we measured, only fatty acid synthase (FAS) was significantly down-regulated by celecoxib treatment. There were no differences in the level of prostaglandin E(2) in these tissues, indicating that celecoxib decreases fat accumulation by down-regulating FAS through a COX-2-independent mechanism. Among the potential molecular targets by which celecoxib may regulate FAS expression, only c-Jun N-terminal kinase-1 (JNK1) was significantly down-regulated. Furthermore, a known inhibitor of JNK suppressed FAS expression in rat hepatocytes. Our observations suggest that celecoxib suppresses FAS expression and decreases fat accumulation by down-regulating JNK1.
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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) | 0.002 | 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".