Hypericin and Hyperforin Production in St. John's Wort in Vitro Culture: Influence of Saccharose, Polyethylene Glycol, Methyl Jasmonate, and<i>Agrobacterium tumefaciens</i>
Bibliographic record
Abstract
Influence of saccharose in the presence or absence of polyethylene glycol (PEG), methyl jasmonate, and an inactivated bacterial culture of Agrobacterium tumefaciens in cultivation medium on morphology of Hypericum perforatum L. and production of hypericin and hyperforin was studied under in vitro conditions. Production of hypericin and hyperforin was influenced by the presence of different concentrations of saccharose (10-30 g L(-1)) in cultivation medium. Addition of PEG (1.25-5 g L(-1)) in the presence of saccharose (10-30 g L(-1)) increased production of hypericin and hyperforin in the H. perforatum in vitro culture. Synthesis of hypericin and hyperforin was unchanged or reduced for most of the experimental plants at higher contents of PEG (10 and 15 g L(-1)). Concentrations of hypericin and hyperforin in the H. perforatum were on the order 100 and 103 microg g(-1) of dry plant material, respectively. Production of hypericin and hyperforin was stimulated either in the presence of a chemical elicitor (methyl jasmonate) or an inactivated bacterial culture of A. tumefaciens. Morphological changes induced by the abovementioned substances were observed and described in detail. The obtained results will be applied in experimental botany and in the technology of H. perforatum cultivation for pharmaceutical applications.
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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) | 0.001 | 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 | 0.001 |
| 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".