TESTING PHARMACEUTICAL RELEASE OF ACTIVE SUBSTANCES FROM MEDICINAL PRODUCTS CONTAINING ST. JOHN'S WORT.
Bibliographic record
Abstract
The aim of this study was to determine the content of hypericins and flavonoids in tablets and capsules containing the extract or powdered herb of St. John's wort, in herbs for infusion and herbal infusions and to release of these compounds from tablets and capsules. HPLC method was used to determine the assay of hypericins and flavonoids in all tested products. The hypericins content was between 0.35 mg and 1.44 mg per tablet or capsule. The release of hypericins from these products in the phosphate buffer of pH 6.8 is between 30 and 60% of the determined content. The degree of hypericins release from herbs into infusions was 15% on average, which corresponds to 0.64 mg of hypericins per infusion of 4 g of herbs. The flavonoids content was between 8.79 and 36.3 mg per tablet or capsule. The release of flavonoids in the phosphate buffer of pH 6.8 is between 63 and 85% of the determined content. The degree of flavonoids release was 76% on average, which corresponds to 77.0 mg per infusion of 4 g of herbs. The test results confirmed that infusions from the St. John's wort constitute are a rich source of flavonoids. At the same time, the universally accepted opinion that aqueous infusions contain only trace amounts of hypericins was not confirmed. Infusions from Herba hyperici may also be a source of hypericins in amounts comparable with the minimum dose recommended for the treatment of mild to moderate depressive episodes.
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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 | 0.001 |
| 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 | 0.000 |
| 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".