In vitro evaluations of cytotoxicity of Abelmoschus esculentus L., Asparagus aphyllus L. and Crataegus azarolus L. extracts and their effects on GLUT4 membrane translocation on L6 muscle cells and blood glucose levels in mice
Bibliographic record
Abstract
Despite the enormous achievements in the development of conventional drugs, herbal-based medicines are still a common practice for the prevention/treatment of diabetes and its related complications. Asparagus aphyllus L. (AA), Abelmoschus esculentus L. (AE) and Crataegus azarolus L. (CA) are recommended in the Greco-Arab traditional medicine for the prevention and treatment of diabetes. The purpose of this study was to evaluate the hypoglycemic effects of ethanolic extracts of these plants in high fat (HF)-induced diabetes in male C57BL/6J mice. Animals were divided into nine groups (four mice per a cage) and treated orally with drinking water without (control group) or with one of the extracts at 50 or 100 mg extract/kg/day (treated groups 2-9) for four weeks. Treatment with AA and AE extracts (100 mg/kg/day of each) for 18 days significantly reduced the blood glucose levels by 33 and 29% compared to control mice, respectievly. CA (both 50 mg/kg/day and 100 mg/kg/day) failed to affect glucose concentration in mice blood throughout the study period. The effects of the plant extracts on glucose transporter-4 (GLUT4) translocation to the plasma membrane was tested in L6 muscle cells, stablely expressing myc epitope at the glucose transporter-4 (L6-GLUT4myc). Exposing of these cells to AA and AE extracts (63 g/ml) led to a significant gain (by about 20%) in GLUT4 on their plasma membranes at non-cytotoxic concentrations as measured with MTT assay where no significat reduction in cell viability were observed up to 250 g/ml. CA failed to increase the GLUT4 translocation. These findings indicate that the observed hypoglycemic properties of these plants are mediated, at least partially, through regulating GLUT4 translocation.
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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 | 0.000 | 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 | 0.001 |
| 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".