Quantification of verbascoside in medicinal species of Phlomis and their genetic relationships
Bibliographic record
Abstract
BACKGROUND: The genus Phlomis (Lamiaceae) is introduced by its valuable medicinal species, of which 17 species are growing wildly and ten of them are exclusively endemic of Iran. The main phytochemical characteristic of this genus is presence of iridoid glycosides including ipolamide, auroside, lamiide and also phenylethanoids such as verbascoside (acetoside) found in Lamiales order.Due to the broad range of biological and pharmacological activities of verbascoside and lack of any report on quantification of this compound within Iranian species of Phlomis, we conducted a research to achieve two main goals, finding a genetic biodiversity by RAPD (Randomly Amplified Polymorphic DNA), as well as detecting and quantifying verbascoside in nine species of Phlomis growing wildly in Iran. RESULTS: The results showed that various samples of P.olivieri possess different genetic distances from each other. Also, various species of P.olivieri display close relationships to P.anisodonta and P. persica. Phytoanalysis of Phlomis species by means of TLC scanner using verbascoside as a phytochemical marker showed that the highest concentration of verbascoside was found in P. anisodonta, however, P. bruguieri and P. olivieri (from Mazandaran) were in the second and third places. Interestingly, the lowest concentration of verbascoside was detected in P. olivieri (from Azerbayjan), exhibiting the effect of various growing areas and conditions on the measured levels of this compound. CONCLUSIONS: verbascoside can be found in various species of Iranian Phlomis, of which P. anisodonta, P. bruguieri and P. olivieri might be the best choices. In addition, although the concentration of verbascoside in these plants may be affected by the growing areas and conditions, there are a good agreement between genetic relations and verbascoside levels.
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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 | 0.001 | 0.001 |
| 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".