Effects of Royal Jelly on Gut Dysbiosis and NAFLD in db/db Mice
Bibliographic record
Abstract
Royal jelly (RJ) is a naturally occurring substance synthesized by honeybees and has various health benefits. Herein, we focused on the medium-chain fatty acids (MCFAs) unique to RJ and evaluated their therapeutic efficacy in treating non-alcoholic fatty liver disease (NAFLD). We examined db/m mice that were exclusively fed a normal diet, db/db mice exclusively fed a normal diet, and db/db mice fed varying RJ quantities (0.2, 1, and 5%). RJ improved NAFLD activity scores and decreased gene expression related to fatty acid metabolism, fibrosis, and inflammation in the liver. RJ regulated innate immunity-related inflammatory responses in the small intestine and decreased the expression of genes associated with inflammation and nutrient absorption transporters. RJ increased the number of operational taxonomic units, the abundance of Bacteroides, and seven taxa, including bacteria that produce short-chain fatty acids. RJ increased the concentrations of RJ-related MCFAs (10-hidroxy-2-decenoic acid, 10-hydroxydecanoic acid, 2-decenedioic acid, and sebacic acid) in the serum and liver. These RJ-related MCFAs decreased saturated fatty acid deposition in HepG2 cells and decreased the gene expression associated with fibrosis and fatty acid metabolism. RJ and RJ-related MCFAs improved dysbiosis and regulated the expression of inflammation-, fibrosis-, and nutrient absorption transporter-related genes, thereby preventing NAFLD.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".