Determination of flavonoid compounds from<i>Saussurea involucrata</i>by liquid chromatography electrospray ionisation mass spectrometry
Bibliographic record
Abstract
Saussurea involucrata produces several bioactive flavonoids that are derived from the phenylpropanoid pathway. To determine these flavonoids, a sensitive high performance liquid chromatography electrospray ionisation mass spectrometry method (LC-ESI-MS) was developed. Chromatographic separation was then performed. The gradient elution was optimised to give high recoveries and satisfactory chromatographic resolution. Flavonoid detection was carried out using an ion trap as mass analyser. Parameters of the mass analyser were optimised. We used the validated LC-ESI-MS method to verify the identities of bioactive compounds, namely apigenin, luteolin, hispidulin, luteolin-7-O-glucoside and rutin. Calibration curves for these five flavonoids were linear in ranges between 5.0 and 500 microg mL(-1). The limit of detection ranged from 1.5 x 10(-4) (for hispidulin) to 6.1 x 10(-3) mg mL(-1) (for rutin). Precision was well within the acceptable range (RSD < 3.0%) and the recovery rate was between 75.3 and 89.8% for each flavonoid. A method validation study showed that the LC/MS technique was a powerful analytical tool for detecting trace amounts of the flavonoid compounds in extracts of S. involucrata.
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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 | 0.001 |
| 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".