Influence of Saskatoon Berry and Cyanidin-3-Glucoside on Gut Microbiota and Relationship with Metabolism and Inflammation in High Fat-High Sucrose Diet-Induced Insulin Resistant Mice
Bibliographic record
Abstract
Abstract Background Type 2 Diabetes (T2D) has become one of most common and harmful chronic diseases worldwide. T2D is characterized as insulin resistant and is often associated with unhealthy dietary habits. The present study assessed the effects of freeze-dried Saskatoon berry powder (SBp) and cyanidin-3-glucoside (C3G, an anthocyanin enriched in SBp) on metabolism, inflammatory markers and gut microbiota in high fat-high sucrose diet (HFHS) diet induced insulin resistant mice. Results Male C57 BL/6J mice received control, HFHS, HFHS + SBp (8.0 g/kg body weight/day) or HFHS + C3G (7.2 mg/kg/day, equal amount of C3G in 8.0 g/kg/day SBp) diet for 11 weeks. HFHS diet significantly increased the levels of glucose, cholesterol, triglycerides, insulin resistance and inflammatory mediators in plasma. The results of 16S rRNA gene sequencing demonstrated that HFHS diet increased the ratio of Bacteroidetes/Firmicutes (B/F) phylum bacteria and an elevated abundance of Muriculaceae family bacteria in the feces of mice. SBp or C3G supplementation attenuated HFHS diet-induced disorders in metabolism and inflammatory markers, and increased B/F ratio and Muriculaceae abundance in mouse gut compared to HFHS diet alone. The abundance of Muriculaceae in the gut microbiota negatively correlated with body weight, glucose, lipids, insulin resistance and inflammatory mediators in mice. The results of functional predication analysis suggest that HFHS diet upregulated the genes of gut bacteria involved in inflammation-related cellular processes, and inhibited bacteria involved in metabolism. SBp and C3G partially neutralized the alterations induced by HFHS diet in gut microbiota implicated in metabolism or inflammation. Conclusion The findings of the present study suggest that SBp is a potential prebiotic food mitigating Western diet-induced disorders in metabolism, inflammation and gut dysbiosis, and C3G possibly contributes to the beneficial effects of SBp.
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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".