A polyphenol-rich cranberry extract reverses insulin resistance and hepatic steatosis independently of body weight loss
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Bibliographic record
Abstract
OBJECTIVE: Previous studies have reported that polyphenol-rich extracts from various sources can prevent obesity and associated gastro-hepatic and metabolic disorders in diet-induced obese (DIO) mice. However, whether such extracts can reverse obesity-linked metabolic alterations remains unknown. In the present study, we aimed to investigate the potential of a polyphenol-rich extract from cranberry (CE) to reverse obesity and associated metabolic disorders in DIO-mice. METHODS: Mice were pre-fed either a Chow or a High Fat-High Sucrose (HFHS) diet for 13 weeks to induce obesity and then treated either with CE (200 mg/kg, Chow + CE, HFHS + CE) or vehicle (Chow, HFHS) for 8 additional weeks. RESULTS: CE did not reverse weight gain or fat mass accretion in Chow- or HFHS-fed mice. However, HFHS + CE fully reversed hepatic steatosis and this was linked to upregulation of genes involved in lipid catabolism (e.g., PPARα) and downregulation of several pro-inflammatory genes (eg, COX2, TNFα) in the liver. These findings were associated with improved glucose tolerance and normalization of insulin sensitivity in HFHS + CE mice. The gut microbiota of HFHS + CE mice was characterized by lower Firmicutes to Bacteroidetes ratio and a drastic expansion of Akkermansia muciniphila and, to a lesser extent, of Barnesiella spp, as compared to HFHS controls. CONCLUSIONS: Taken together, our findings demonstrate that CE, without impacting body weight or adiposity, can fully reverse HFHS diet-induced insulin resistance and hepatic steatosis while triggering A. muciniphila blooming in the gut microbiota, thus underscoring the gut-liver axis as a primary target of cranberry polyphenols.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it