Use of digitoxin and digoxin as internal standards in HPLC analysis of triterpene saponin‐containing extracts
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Saponins are widely distributed complex plant glycosides possessing a variety of structure-dependent bioactivities. Quantitation of individual saponins is difficult due to lack of available standards, mainly as a consequence of purification difficulties. Determination of total saponin content can be problematic, often relying on non-specific methods based on butanol solubility, haemolytic activity or formation of coloured derivatives. OBJECTIVE: To develop a general quantitative method based on the use of the readily available cardenolides, digitoxin (1) and digoxin (2), as internal standards in an HPLC-PAD-based analysis. METHODOLOGY: The cardenolides were run at a variety of concentrations to establish linearity and reproducibility of detector response and then evaluated as internal standards for quantitation of triterpene saponins in several plant-derived extracts by HPLC-PAD. Mixtures of saponins, largely freed from other extractables, were obtained by fractionation of total extracts on solid phase extraction columns (SPE) employing a water-methanol gradient and used for construction of calibration curves. Saponin identification and structural information was obtained via a single quadrupole mass detector using electrospray ionisation in negative ion mode (ESI(-)). RESULTS: Saponin contents in six samples from five species were determined and compared with literature results and a gravimetric method based on butanol-water partitioning. Results were generally consistent with literature reports and superior to gravimetric butanol-water partitioning. CONCLUSION: Digitoxin and digoxin are useful as internal standards in HPLC estimation of saponin content. Saponins from different species having similar structures and molecular weights afford similar calibration curves.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it