Determination of mangiferin in Mangifera indica L. stem bark extract (Vimang®) and pharmaceuticals by liquid chromatography
Bibliographic record
Abstract
A new liquid chromatography method for the analysis of mangiferin (I) from Mangifera indica L. stem bark extract (Vimang®), and pharmaceuticals is described. Screening experiments were performed by an experimental design to find the influence of some important chromatographic variables (methanol, column temperature and acetic acid) on the retention times and resolution between critical pairs in the separation. This design also permitted to estimate method robustness and optimal conditions to achieve the best resolution. The best separation was found using a LiChrospher RP 18, 5 µm, 250 x 4.6 mm I.D. column maintained at 25°C, a mobile phase comprising methanol-2.5% v/v aqueous solution of acetic acid (280:720, v/v) at a flow rate of 1.0 ml/min, and detection by UV at 254 nm. The method resolves I, the major component, from other components of the extract. The method showed good selectivity, repeatability (RSD < 2%) and linearity (r = 0.9998). The limits of detection and quantitation were 0.008% (0.9 ng) and 0.05% (6.2 ng), respectively, relative to a 0.6 mg/ml standard solution, injection volume 20 µl. This method was used to quantify I in some aqueous extracts from the natural product and pharmaceuticals.
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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 | 0.001 |
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".