EXTRACTION OF HYPERFORIN AND HYPERICIN FROM ST. JOHN'S WORT (<i>HYPERICUM PERFORATUM</i> L.) WITH DIFFERENT SOLVENTS
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Bibliographic record
Abstract
ABSTRACT The extraction of St. John's wort ( Hypericum perforatum L.) was carried out with different solvents to obtain valuable components and natural agents rich extracts. Further aim of this study was to compare the raw materials that were gathered at the beginning and the end of the blossoming. For the laboratory Soxhlet extraction of St. John's wort four different solvents (n‐hexane, ethyl acetate, 2‐propanol, ethanol) were applied. Increasing the polarity of solvents higher extraction yields were achieved (43–360 g/kg). Pilot plant experiments were performed in a 5·10 ‐ 3 m 3 volume Soxhlet extractor with ethanol and in a 5·10 ‐ 3 m 3 volume high‐pressure vessel at 313K and 45 MPa with supercritical CO 2 . The extract samples were analyzed by UV‐visible spectrophotometry and high‐performance liquid chromatography methods. The effective extraction of both main compounds (hypericin and hyperforin) was achieved. The sample gathered at the end of the blossoming extracted with nonpolar solvent (sc‐CO 2 ) at mild temperature (∼313K) provided stable hyperforin rich extract. The sample gathered at the begining of the blossoming extracted with polar solvent (ethanol) at mild temperature (∼313K) provided stable hypericin rich extract. PRACTICAL APPLICATIONS Hypericum perforatum (St. John's wort) is among the favorite herbal drugs, and is the only herbal alternative to classical synthetic antidepressants, in the therapy of mild‐to‐moderate depression. Several studies describe that the active ingredients in St. John's wort are hypericin and hyperforin, which inhibit the reuptake of monoamines, including serotonin, noradrenalin and dopamine, as well as the amino acid neurotransmitters γ ‐aminobutiric acid and glutamate. The results from this study can be used for produce a stable hyperforin‐rich extract and a stable hypericin rich extract. These extracts can be utilized for a production of food supplement herbal preparations which standardized on both main compounds.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it