Dietary Intervention with Resistant Starch-Rich Unripe Plantain Flour Restores Gut Microbiome–Metabolome Axis and Ameliorates Type 2 Diabetes in Rats
Bibliographic record
Abstract
Plantain (Musa spp., AAB group) possesses a complex triploid genetics originating from interspecific hybridization, which underlies its agronomic traits and nutritional composition, making it a vital global staple food crop. Unripe plantain flour (UPF), a rich source of resistant starch (RS), has demonstrated anti-diabetic properties in diabetic rats, yet its mechanisms of action remain unclear. This study investigated whether unripe plantain flour attenuates type 2 diabetic traits in rats made diabetic with a high-fat diet plus streptozotocin through regulation of the gut microbiome–metabolome axis, including short-chain fatty acids and bile acids. We found that UPF intervention significantly ameliorated gut microbiota dysbiosis. It enriched beneficial bacteria, particularly SCFA producers (Lachnoclostridium, Blautia, Butyricicoccus) and others (Bifidobacterium, Akkermansia), while inhibiting harmful genera (Romboutsia, Allobaculum). Consequently, UPF altered bile-acid composition by lowering hydrophobic species (e.g., cholic acid and deoxycholic acid) while elevating hydrophilic species (e.g., ursodeoxycholic acid and tauroursodeoxycholic acid). It also enhanced the excretion of secondary bile acids (lithocholic acid). These coordinated changes in the gut ecosystem are conducive to improved glycolipid metabolism. Spearman correlation analysis further reinforced the close relationships between the altered microbiota and metabolites. Our results elucidate that UPF exerts its anti-diabetic effects by remodeling the gut microbiota and modulating its associated metabolites, highlighting a novel dietary intervention strategy for diabetes management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".