Flaxseed lignan secoisolariciresinol diglucoside improves insulin sensitivity through upregulating GLUT4 expression in diet‐induced obese mice (829.25)
Bibliographic record
Abstract
Flaxseed Lignan Secoisolariciresinol Diglucoside Improves Insulin Sensitivity through Upregulating GLUT4 Expression in Diet‐Induced Obese Mice Yanwen Wang 1 , Bourlaye Fofana 2 , Moumita Roy 1 , and Kaushik Ghose 2 1 Aquatic and Crop Resource Development, National Research Council of Canada, Charlottetown, PE, Canada C1A 4P3 2 Agriculture and Agri‐Food Canada, Charlottetown, PE, Canada C1A 4P3 The objective of this study was to determine the anti‐diabetic effect and underlying mechanisms of flaxseed lignans in diet‐induced obese and insulin resistant mice. Male C57BL/6J mice, at the age of 8 wk, were provided with a high‐fat diet to induce insulin resistance. The age‐matched male C57BL/6J mice fed in parallel with a low‐fat diet were used as the normal control. After 12 wk, the high‐fat diet‐fed mice were randomized into 4 groups and treated by gavage feeding once a day with 0 (high‐fat/insulin resistant control), 10, 100, and 1,000 mg/kg/d of secoisolariciresinol diglucoside (SDG, 60% pure) lignan dissolved in water, respectively, for 6 weeks. The high‐fat and low‐fat control groups were gavaged with the vehicle. It was demonstrated that oral administration of SDG lowered body weight, serum insulin, total cholesterol and free fatty acid levels. SDG also improved oral glucose tolerance and insulin tolerance. Further molecular experiments showed that SDG increased muscle GLUT4 protein expression. The results suggest that flaxseed SDG lignan protects from insulin resistance in diet‐induced obese mice and has potential to be used as a natural product for the prevention and treatment of obesity‐related insulin resistance or diabetes. Grant Funding Source : TUFGEN 604381
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".