Genistein Reduces Hyperglycemia and Islet Cell Loss in a High-Dosage Manner in Rats With Alloxan-Induced Pancreatic Damage
Bibliographic record
Abstract
OBJECTIVES: Elucidate whether genistein (a soy-derived isoflavone) possesses the capacity to alleviate hyperglycemia and minimize islet cell loss after the onset of diabetes and whether the beneficial effect of genistein is dosage dependent. METHODS: Alloxan-induced diabetic male Sprague-Dawley rats were randomly divided into 5 groups (10 rats per group) and treated with saline, vehicle, and 3 different dosages of genistein by daily gavage. Blood glucose and insulin levels, body weight, and oral glucose tolerance test were assessed; histological changes in pancreatic islets were quantified. In addition, rat islets were isolated, cultured, and exposed to alloxan in the presence or absence of genistein. The survival and the proliferation of islet cells were assessed, and insulin levels in the culture supernatant were measured. RESULTS: In vivo high-dose (30 mg/kg per day) but not low-dose genistein significantly decreases weight loss, hyperglycemia, and islet cell loss in alloxan-induced diabetic rats, while increasing blood insulin levels and glucose tolerance. In vitro experiments reveal that genistein improves islet cell survival and proliferation and facilitates insulin production after alloxan injury. CONCLUSIONS: Genistein possesses the capacity to reduce hyperglycemia via minimization of islet cell loss in a dosage-dependent manner (estimating >5-fold than physical intakes) after the onset of diabetes.
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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) | 0.001 | 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".