Bio-guided Isolation of Antioxidant Compounds from Chrysophyllum perpulchrum, a Plant Used in the Ivory Coast Pharmacopeia
Bibliographic record
Abstract
Chrysophyllum perpulchrum (Sapotaceae) is used in the traditional Ivory Coast pharmacopeia to cure fevers. The extract of C. perpulchrum used for this study was the powdered form obtained from the maceration of the dried plant bark in 96% methanol, followed by evaporation to dryness. In the present study, the antioxidative and radical-scavenging activities of the methanolic extract were studied with three standard biological tests: DPPH reduction, ferric thiocyanate (FTC) lipidic peroxidation inhibition and thiobarbituric acid reacting substances (TBARS). Gallic acid and quercetin were used as references. The total amount of phenolic compounds in the extract was determined by ultraviolet (UV) spectrometry and calculated as gallic acid equivalents. Catechin and two dimeric procyanidins were found to be the compounds responsible for the activities. They were chemically dereplicated in the extract by LC-MS. For quantitation purposes, they were isolated by successive chromatographic methods and characterized by mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectrometry. The quantities of these compounds in C. perpulchrum were 5.4% for catechin (P1), and 5.6 and 9.2% for dimers (compounds 2 (P2) and 3 (P3)), respectively. They displayed antioxidant activity with IC(50) values of 2.50 ± 0.15 µg/mL (P1), 2.10 ± 0.2 µg/mL (P2) and 2.10 ± 0.1 µg/mL (P3). The total extract, the active fractions and the pure compounds inhibited the lipid peroxidation by the FTC method and the TBARS method in the range of 60%. These values were comparable to those seen for quercetin.
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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 | 0.001 |
| 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".