Optimized and Validated HPLC Analysis of St. John's Wort Extract and Final Products by Simultaneous Determination of Major Ingredients
Bibliographic record
Abstract
Aim of this work was to develop a validated high performance liquid chromatography method for the analysis of extracts and final products of St. John's wort, according to international guidelines for bioanalytical method validation. Chromatographic separation was performed on a C18 column with a combination of gradient and isocratic steps; the mobile phase composed of ammonium acetate solution (pH 4.5; 10 mM), acetonitrile and methanol. Quantification and method validation was performed using extract spiked with external reference standards of chlorogenic acid, rutin, hyperoside, isoquercitrin, quercetin and hypericin. Validation study revealed that trans-chlorogenic acid is partially transformed into its cis-isomer during analysis. The method showed good linearity, precision and accuracy. Hyperforin was completely unstable. All other ingredients were stable at -18°C and after three freeze-thaw cycles, while stability of most ingredients was limited at room temperature and 4 - 8°C; quercetin was the most unstable one. The major ingredients of methanolic extracts, infusions and final products of Hypericum perforatum were completely resolved and quantified. Beyond its potential usefulness in the analysis of St. John's wort products, this study addresses the issue of validation from the perspective of the field of bioanalysis and reveals the wealth of critical information which can be derived.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".