Purification of Danshensu from <i>Salvia miltiorrhiza</i> Extract Using Graphene Oxide-Based Composite Adsorbent
Bibliographic record
Abstract
Danshensu has generated significant interest due to its therapeutic properties as a cardiovascular, antitumor, and neurology drug. Column chromatography techniques that are currently used for the separation of danshensu from Salvia miltiorrhiza extract have some drawbacks such as high pressure drop, slow separation, and the need for organic solvents. We discuss the use of a novel composite adsorbent consisting of graphene oxide (GO)-modified cotton fiber for danshensu purification at high flow rate and low back pressure. This adsorbent was prepared by directly grafting GO onto the surface of cotton fiber. Danshensu was purified from aqueous Salvia miltiorrhiza extract based on hydrophobic interaction in a flow-through mode. The adsorbent could then be regenerated by elution of bound impurities using 0.04 M NaOH solution. HPLC analysis showed that the purity of danshensu increased from 24.8% in the feed solution (crude aqueous extract) to about 70–75% in the purified danshensu sample, the recovery being greater than 96.0%. Adsorbent fouling was minimal as indicated by the low back pressure at the end of the process.
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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) | 0.000 | 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) | 0.001 | 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".