Rapid fingerprint analysis for herbal polysaccharides using direct analysis in real‐time ionization mass spectrometry
Bibliographic record
Abstract
RATIONALE: Herbal polysaccharides have various potential medicinal values. Development of reliable analytical method for the fingerprint analysis of polysaccharides is critical for their quality assessment, origin identification, and authenticity evaluation. METHODS: Mechanochemical extraction (MCE) was used to extract polysaccharide components from different herbal species. Intact polysaccharides were then directly analyzed by direct analysis in real-time mass spectrometry (DART-MS). Standard addition method with isotope-labeled internal standard was used to quantify polysaccharide amounts directly from liquid extract. Multivariate data analysis was further conducted for species classification. RESULTS: The intact and large polysaccharides were decomposed into small fragment ions less than m/z 350 instantaneously using DART ion source. Different polysaccharides showed distinguished fingerprint DART-MS spectra using both individual and mixed herbal species. The liquid supernatant from MCE was validated to be used as direct sample for DART-MS analysis. Quantitation was successfully achieved for polysaccharide contents in Dendrobium officinale from different locations. CONCLUSIONS: A rapid fingerprint protocol in combination of MCE and DART-MS for herbal polysaccharides was developed. The whole process could be accomplished within a few minutes, from raw materials to final spectra, without requirements of pre-digestion and additional sample purification.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.014 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".