Purification of Phenylalkanoids and Monoterpene Glycosides from <i>Rhodiola rosea</i> L. Roots by High‐speed Counter‐current Chromatography
Bibliographic record
Abstract
INTRODUCTION: Rhodiola rosea L. is a medicinal herb used for its adaptogenic properties. The main active components are the phenylpropanoids collectively referred to as rosavins. OBJECTIVES: To develop an isolation method for phytochemicals present in Rhodiola rosea roots using high-speed counter-current chromatography (HSCCC). METHODOLOGY: The roots of Rhodiola rosea were extracted with methanol and fractionated using liquid-liquid partition and polyamide column clean-up. The purified fraction (100 mg) was subjected to semi-preparative HSCCC using the two-phase solvent system ethyl acetate:butanol:water (3:2:5). The head-to-tail elution mode was employed with a flow rate of 1.5 mL/min and a rotary speed of 1000 rpm. RESULTS: The separation yielded six main fractions with four components more than 90% pure. The sixth fraction was further purified using semi-preparative HPLC with a Synergi-hydro RP C₁₈ -column to obtain rosin and geranyl 1-O-α-l-arabinopyranosyl(1 → 6)-β-d-glucopyranoside. The main components isolated were rosavin (3.4 mg, 97% purity), salidroside (0.5 mg, 90% purity), benzyl-O-β-d-glucopyranoside (1.2 mg, 85% purity), rosarin (1.3 mg, 99% purity), rosiridin (1.8 mg, 92% purity), rosin (1.2 mg, 95% purity) and geranyl 1-O-α-l-arabinopyranosyl(1 → 6)-β-d-glucopyranoside (6.5 mg, 97% purity). The identity and purity of these components were confirmed using ultrafast liquid chromatography-diode-array detector-MS/MS analysis, ¹H- and ¹³C-NMR spectroscopy. CONCLUSION: High-speed counter-current chromatography was successful in the isolation of several phytochemicals present in Rhodiola rosea roots, including two components that are not commercially available.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.001 |
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".