Isolation and fast analysis of phytochemical constituents in Echinacea species and Rhodiola rosea L. using high-speed counter-current chromatography and ultra fast liquid chromatography-mass spectrometry
Bibliographic record
Abstract
High-speed counter-current chromatography was used for the purification of phytochemical components from the roots of Echinacea angustifolia (DC.) Hell and Rhodiola rosea L. Five alkylamides were purified from Echinacea angustifolia roots using two solvent systems and seven phenylalkanoid and monoterpene glycosides were isolated from Rhodiola rosea roots using one solvent system and semi-preparative HPLC. Fast analytical methods were developed for the identification of alkylamides in Echinacea roots and commercial products available in the Canadian marketplace. 24 alkylamides were identified in 15 minutes using ultra-fast liquid chromatography with diode array and mass spectrometric detection. The three major alkylamides obtained by HSCCC were used as quantitative standards to determine alkylamide contents in different products. Also, a 22 minute method using UFLC-DAD-MS was developed for the characterization of 27 components in Rhodiola rosea roots. These techniques can be used in quality and authenticity control of natural health products containing Echinacea and Rhodiola rosea.
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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 | 0.000 |
| 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 | 0.000 |
| 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".