The effect of cannabinoid receptor 1 blockade on adipokine and proinflammatory cytokine concentration in adipose and hepatic tissue in mice with nonalcoholic fatty liver disease
Bibliographic record
Abstract
In high-fat diet (HFD) induced nonalcoholic fatty liver disease (NAFLD), there is an increase in the endocannabinoid system activity, which significantly contributes to steatosis development. The aim of our study was to investigate the effects of cannabinoid receptor type 1 blockade on adipokine and proinflammatory cytokine content in adipose and hepatic tissue in mice with NAFLD. Male mice C57BL/6 were divided into a control group fed with a control diet for 20 weeks (C, n = 6) a group fed with a HFD for 20 weeks (HF, n = 6), a group fed with a control diet and treated with rimonabant after 18 weeks (R, n = 9), and a group fed with HFD and treated with rimonabant after 18 weeks (HFR, n = 10). Rimonabant significantly decreased leptin, resistin, apelin, visfatin, interleukin 6 (IL-6), and interferon-γ (IFN-γ) concentration in subcutaneous and visceral adipose tissue in the HFR group compared to the HF group (p < 0.01). Rimonabant reduced hepatic IL-6 and IFN-γ concentration as well as plasma glucose and insulin concentration and the homeostatic model assessment index in the HFR group compared to the HF group (p < 0.01). It can be concluded that the potential usefulness of CB1 blockade in the treatment of HFD-induced NAFLD is due to modulation of the adipokine profile and proinflammatory cytokines in both adipose tissues and liver as well as glucose metabolism.
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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) | 0.001 | 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) | 0.001 | 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".