St. John's Wort Hypericum perforatum L.: Supercritical extraction, antimicrobial and antidepressant activity of extract and some component
Bibliographic record
Abstract
St. John's Wort, the Hypericum perforatum L. is one of the most analyzed plant species today. Plant was characterized with a wide ecological spectrum and is a plant with beautiful yellow flowers. St. John's Wort was used and still is in used in traditional medicine all over the World. Many bioactive components from St. John's Wort like hypericine, hyperforine, qercetrine and essential oil, were isolated and have been used in medicine. The most popular use of Hipericum extract is as an antidepressant for the medicinal treatment of mild and high depression. The medical use of hyperforine in photodynamic therapy for cancer treatment has now been intensively analyzed. The extract of St. John's Wort showed high antimicrobial, even on pathogenic microorganisms as well as antiviral activity. The use of bioactive components from St. John's Wort depends on the possibility to isolate them in the pure state. It seems that supercritical extraction with carbon dioxide might to be the best solution for obtaining pure extract as well as some of the components present in the essential oil and extract of St. John's Wort. Such a conclusion is supported by the many results of recently performed and published in scientific journals.
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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) | 0.000 | 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) | 0.002 | 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".