Anti-diabetic compounds from Uvaria dulcis Dunal
Bibliographic record
Abstract
Medicinal plants have long been a source of lead compounds for drug discovery. Among these, the Annonaceae family has gained recognition for its potential to yield novel compounds, particularly those that can be used in the development of drugs targeting chronic diseases like diabetes mellitus (DM). We employed various chromatographic methods to isolate bioactive compounds from the roots, leaves, and twigs of Uvaria dulcis Dunal. We used spectroscopic methods to determine the chemical structures of these compounds. We successfully identified twelve known compounds from various parts of U. dulcis : patchoulenon, polygochalcone, 2′3′-dihydroxy-4′,6′-dimethoxydihydrochalcone, 2′,3′-Dihydroxy-4′,6′-dimethoxychalcone, Chrysin, Techochrysin, 8-hydroxy-5,7-dimethoxyflavanone, pinocembrin, 3-farnesylindole, onysilin, cinchonain la, and cinchonain lb. Interestingly, cinchonain la and cinchonain lb exhibited more potent anti-α-glucosidase activity than acarbose (standard drug), with IC 50 values of 11.88 ± 1.41 μg/mL and 15.18 ± 1.19 μg/mL, respectively. Cinchonain la inhibited the DPP-IV enzyme, with IC 50 value lower than the standard compound (diprotin A) at 81.78 ± 1.42 μg/mL. While 2′,3′-dihydroxy-4′,6′-dimethoxychalcone show more potent inhibitory effect than standard drug with IC 50 value of 8.62 ± 1.19 μg/mL. Additionally, at a concentration of 10 μg/mL, cinchonain lb and 2′,3′-dihydroxy-4′,6′-dimethoxychalcone promoted glucose uptake in L6 myotubes cells to the same extent as 100 nM insulin. These findings suggest that cinchonain la, cinchonain lb, and 2′,3′-dihydroxy-4′,6′-dimethoxychalcone are the U. dulcis -derived bioactive compounds that hold promise as potential structures to use in the development of anti-diabetic drugs.
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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 | 0.000 |
| 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".