Research on Concentration of Ginsenoside in Different Medical Parts of Panax quinquefolium by HPLC-MS~n
Bibliographic record
Abstract
Objective: High-performance liquid chromatography array mass spectrometry(HPLC-MS) method was developed for determination of the concentration of 10 different ginsenosides of different medical parts of Panax quinquefolium,which collected from original habitat in Ontario of Canada.Method: Sample solution was separated on a DIKMA diamonsil(4.6 mm × 250 mm,5 μm).Acetonitrile-0.05% phosphoric acid aqueous solution and acetonitrile-0.05% acetic acid aqueous solution were used as mobile phase and the flow rate through the HPLC column was 0.3 mL.min-1 and the entire effluent was directed to the mass spectrometer.The column temperature was kept at 35 ℃ and the UV detection wavelength was set at 203 nm.MS analysis was monitored in positive mode.The conditions of ESI source were as follows: sheath gas flow rate,10 L.min-1;sweep gas flow rate,10 L.min-1;spray voltage,4.5 kV;capillary temperature,320 ℃;capillary voltage 30 V.Result: All calibration curves showed good linearity(r 0.999) within the test ranges.The average recovery of the method was between 95% and 102%,RSD 2.68%.The concentration of single ginsenoside of root,stem and leaf was quite different;that of Re and Rb1 of root and that of Rb2 and Rb3 of leaf was higher than others;that of stem was lower than that of root and leaf,moreover that of some samples of leaf was higher than that of root.Conclusion: The method is simple,accurate,replicate and suitable for the determination of P.quinquefolium.It is suggested that the leaf of P.quinquefolium can be used a new resource of ginsenoside.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".