Genistein ameliorates hyperglycemia in a mouse model of nongenetic type 2 diabetes
Bibliographic record
Abstract
While peripheral insulin resistance is common during obesity and aging in mice and people, the progression to type 2 diabetes (T2D) is largely due to loss of β-cell mass and function through apoptosis. We recently reported that genistein, a soy derived isoflavone, can improve glycemic control and β-cell function in insulin-deficient diabetic mice. However, whether it can prevent β-cell loss and diabetes in T2D mice is unknown. Our current study aimed to investigate the effect of dietary supplemented genistein in a nongenetic T2D mouse model. Nongenetic, middle-aged obese diabetic mice were generated by high fat diet and a low dose of streptozotocin injection. The effect of dietary supplementation of genistein on glycemic control and β-cell mass and function was determined. Dietary intake of genistein (250 mg·kg(-1) diet) improved hyperglycemia, glucose tolerance, and blood insulin level in obese diabetic mice, whereas it did not affect body weight gain, food intake, fat deposit, plasma lipid profile, and peripheral insulin sensitivity. Genistein increased the number of insulin-positive β-cell in islets, promoted islet β-cell survival, and preserved islet mass. In conclusion, dietary intake of genistein could prevent T2D via a direct protective action on β-cells without alteration of periphery insulin sensitivity.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".