Two antihyperglycaemic compounds from Globimetula braunii (Engl.) Van Tiegh (Loranthaceae)
Bibliographic record
Abstract
Large numbers of medicinal plants are constantly being screened for possible pharmacological values, especially for chronic diseases such as diabetes, with the view of discovering new compounds that may serve as templates for synthesis of more active/less toxic drugs. Therefore, the antihyperglycaemic activity of the leaf of Globimetula braunii with antidiabetic ethnomedical usage in Nigeria was investigated is this study to justify this folkloric claim. The median lethal dose, LD50 of the ethanol leaf extract of G. braunii was determined using Lorke’s method and its antihyperglycaemic effect at 100, 200 and 400 mg/kg was evaluated using glucose-induced hyperglycaemic rats while glibenclamide (5 mg/kg) and 1 % Tween 80 in normal saline served as positive and negative controls, respectively. Anti-hyperglycaemic activity-directed purification of the extract of the plant in glucose-loaded rats, led to the isolation and characterisation of phyllanthone and methyl 2, 6-dihydroxy-4-methoxybenzoate from the dichloromethane partitioned fraction. The findings showed that the LD50 of the ethanol leaf extract of G. braunii was greater than 5,000 mg/kg while its 100 mg/kg was the most active dose with comparable activity (p>0.05) to the standard drug, glibenclamide. The dichloromethane and aqueous partitioned fractions of the extract were the most promising fractions. Chromatographic separations of the dichloromethane fraction yielded phyllanthone, and methyl 2, 6-dihydroxy-4-methoxybenzoate that elicited comparable activity to glibenclamide (5 mg/kg) at 10 and 20 mg/kg at all time-points. The study justified the antidiabetic folkloric use of G. braunii leaf and confirmed phyllanthone and methyl 2,6-dihydroxy-4-methoxybenzoate as two of its antihyperglycaemic constituents.
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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 | 0.002 |
| 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".