Metformin and Gegen Qinlian Decoction boost islet α-cell proliferation of the STZ induced diabetic rats
Bibliographic record
Abstract
BACKGROUND: The traditional Chinese medicine Gegen Qinlian Decoction (GQD), as well as metformin, had been reported with anti-diabetic effects in clinical practice. OBJECTIVE: To verify whether these two medicines effectively ameliorate hyperglycemia caused by deficiency of islet β-cell mass which occurs in both type 1 and type 2 diabetes. METHODS: SD rats were injected with a single dose of STZ (55 mg/kg) to induce β-cell destruction. The rats were then divided into control, diabetes, GQD and metformin group. GQD and metformin groups were administered with GQD extract or metformin for 6 weeks. The islet α-cell or β-cell mass changes were tested by immunohistochemical and immunofluorescent staining. The potential targets and mechanisms of GQD and metformin on cell proliferation were tested using in silico network pharmacology. Real-time PCR was performed to test the expression of islet cells related genes and targets related genes. RESULTS: Both GQD and metformin did not significantly reduce the FBG level caused by β-cell mass reduction, but alleviated liver and pancreas histopathology. Both GQD and metformin did not change the insulin positive cell mass but increased α-cell proliferation of the diabetic rats. Gene expression analysis showed that GQD and metformin significantly increased the targets gene cyclin-dependent kinase 4 (Cdk4) and insulin receptor substrate (Irs1) level. CONCLUSION: This research indicates that GQD and metformin significantly increased the α-cell proliferation of β-cell deficiency induced diabetic rats by restoring Cdk4 and Irs1 gene expression.
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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 | 0.000 | 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) | 0.001 | 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 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".