Camu-camu decreases hepatic steatosis and liver injury markers in overweight, hypertriglyceridemic individuals: A randomized crossover trial
Bibliographic record
Abstract
Non-alcoholic fatty liver disease (NAFLD), recently referred to as “metabolic dysfunction-associated steatotic liver disease” (MASLD), affects 25% of the adult population with no effective drug treatments available. Previous animal studies reported that a polyphenol-rich extract from the Amazonian berry camu-camu (CC) prevented hepatic steatosis in a mouse model of diet-induced obesity. This study aims to determine the impact of CC on hepatic steatosis (primary outcome) and evaluate changes in metabolic and gut microbiota profiles (exploratory outcomes). A randomized, double-blind, placebo-controlled crossover trial is conducted on 30 adults with overweight and hypertriglyceridemia, who consume 1.5 g of CC capsules or placebo daily for 12 weeks. CC treatment decreases liver fat by 7.43%, while it increases by 8.42% during the placebo intervention, showing a significant difference of 15.85%. CC decreases plasma aspartate and alanine aminotransferases levels and promotes changes in gut microbiota composition. These findings support that polyphenol-rich prebiotic may reduce liver fat in adults with overweight, reducing the risk of developing NAFLD. • Camu-camu reduces hepatic steatosis in adults with overweight and hypertriglyceridemia • Camu-camu supplementation decreases plasma AST and ALT levels • Camu-camu supplementation alters gut microbiota composition Agrinier et al. demonstrate that camu-camu (CC) supplementation reduces liver fat and improves liver injury markers in individuals with overweight and hypertriglyceridemia. CC also alters gut microbiota composition, supporting its potential as a polyphenol-rich prebiotic supplement for reducing non-alcoholic fatty liver disease risk.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.002 | 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 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".