Hypoglycemic and hypolipidemic effects of blueberry anthocyanins by AMPK activation: In vitro and in vivo studies
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Bibliographic record
Abstract
Blueberries are rich in bioactive anthocyanins, with a high level of malvidin, which is associated with antioxidant benefits that contribute to reducing the risk of diabetes. The objective of this study was to investigate the hypoglycemic and hypolipidemic effects of blueberry anthocyanin extract (BAE), malvidin (Mv), malvidin-3-glucoside (Mv-3-glc), and malvidin-3-galactoside (Mv-3-gal) in both human hepatocarcinoma cell line HepG2 and in a high-fat diet combining streptozotocin-induced diabetic mice. High glucose treatment significantly increased hepatic oxidative stress up to 6-fold and decreased HepG2 cell viability. Pretreatment with BAE, Mv, Mv-3-glc and Mlv-3-gal significantly mitigated these damages by lowering the reactive oxygen species (ROS) by 87, 80, 76, and 91%, and increasing cell viability by 88, 79, 73, and 98%, respectively. These pretreatments also effectively inhibited hyperglycemia and hyperlipidemia, respectively by reducing the expression levels of enzymes participating in gluconeogenesis and lipogenesis and enhancing those involved in glycogenolysis and lipolysis, via adenosine monophosphate-activated protein kinase (AMPK) signaling pathway in HepG2 cells. To determinate the role of AMPK in BAE-induced reaction of glucose and lipid metabolism in vivo, doses of 100 mg/kg (blueberry anthocyanin extracts - low concentration, BAE-L) and 400 mg/kg (blueberry anthocyanin extracts - high concentration, BAE-H) were administrated per day to diabetic mice for 5 weeks. BAE treatments had a significant (P < 0.05) effect on body weight and increased the AMPK activity, achieving the decrease of blood- and urine-glucose, as well as triglyceride and total cholesterol. This research suggested that anthocyanins contributed to the blueberry extract-induced hypoglycemia and hypolipidemia effects in diabetes and BAE could be a promising functional food or medicine for diabetes treatment.
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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