Rice bran attenuated obesity <i>via</i> alleviating dyslipidemia, browning of white adipocytes and modulating gut microbiota in high-fat diet-induced obese mice
Bibliographic record
Abstract
Obesity has become an international public health problem. In this study, an obese mice diet was supplemented with raw rice bran (RRB) or infrared radiation-stabilized rice bran (IRRB) to investigate the attenuation of obesity induced by a high-fat diet. Mice were fed a normal diet or a high-fat diet with and without rice bran supplementation (300 mg per kg body weight per day) by oral gavage for 39 days to investigate the obesity preventive effect. The results indicate that different rice bran supplements reduced body weight, relative adipose tissue weight, inflammation, and serum parameters, and relieve liver steatosis to varying degrees. The data of real-time qPCR and western blots (WB) showed that rice bran activated brown adipose tissue (BAT) and increased white adipose tissue (WAT) browning. Rice bran also reduced the ratio of Firmicutes/Bacteroidetes and enhanced the relative abundance of Akkermansia. In summary, our findings suggest that rice bran intervention played a significant role in reducing dyslipidemia, alleviating inflammation, enhancing thermogenesis and modulating gut microbiota for the prevention and control of obesity.
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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 | 0.000 | 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".