Determination of bergenin in ardisia japonica by molecularly imprinted- matrix solid phase dispersion extraction
Bibliographic record
Abstract
A simple method based on matrix solid-phase dispersion using molecularly imprinted polymers as the sorbent was developed for selective extraction of bergenin from Ardisia japonica. The MIPs were synthesized using bergenin as a template molecule, methacrylic acid as a functional monomer, and ethylene glycol dimethacrylate as a cross-linking agent. The polymers have been characterized by scanning electron microscopy and Fourier-transform infrared spectrometry. The maximum extraction yield of bergenin was obtained with the optimized extraction conditions: 2/1 as the ratio of MIPs to the sample; 8 min as the dispersion time; 10%aqueous methanol as a washing solvent and methanol-acetic acid( 99: 1,V/V) as an elution solvent. The extract obtained was analyzed by high performance liquid chromatography. The result obtained by this method was compared with that obtained by methanol extraction used in Chinese Pharmacopoeia. The results indicated that the extraction yield of bergenin obtained by MIP-MSPD was higher than that obtained by methanol extraction. Moreover,the consumption of the organic solvent and extraction time were reduced in our method,and the selectivity was also improved.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 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".