Islet protective and insulin secretion property of<i>Murraya koenigii</i>and<i>Ocimum tenuflorum</i>in streptozotocin-induced diabetic mice
Bibliographic record
Abstract
The present study investigates the antidiabetogenic effects of Murraya koenigii (L.) Spr. and Ocimum tenuflorum L. on streptozotocin-induced diabetic Swiss mice. Treatment with extracts of M. koenigii (chloroform; MKC) and O. tenuflorum (aqueous; OTA) resulted in proper glucose utilization with an increase in liver glucose-6-phosphate dehydrogenase enzyme activity, and normal glycogenesis in hepatic and muscle tissues. Pancreatic and intestinal glucosidase inhibitory activity observed with MKC and OTA treatment indicated beneficial effects in reducing postprandial hyperglycemia with concomitant improvement in glucose metabolism. The glucosidase inhibition was prolonged, even after discontinuation of MKC and OTA treatment. Normalization of plasma insulin and C-peptide levels was observed in diabetic mice, indicating endogenous insulin secretion after treatment. The histochemical and immunohistochemical analysis of pancreatic islets suggests the role of MKC and OTA in pancreatic β-cell protection and the functional pancreatic islets that produce insulin. The study demonstrates the significance of MKC and OTA in glucosidase inhibition and islet protection in the murine diabetic model. These findings suggest the potential of the extracts in adjuvant therapy for the treatment of diabetes and the possible development of potential neutraceuticals.
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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) | 0.000 | 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 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".