Polysaccharides of <i>Scrophularia ningpoensis</i> Hemsl.: Extraction, Antioxidant, and Anti‐Inflammatory Evaluation
Bibliographic record
Abstract
The roots of Scrophularia ningpoensis Hemsl. are a famous traditional Chinese medicinal herb and are also used as health food. However, information about polysaccharides from S. ningpoensis (SNPS) is very limited. We applied the ultrasonic‐assisted extraction (UAE) process to extract SNPS. The UAE conditions were optimized using single‐factor experiments and response surface analysis. Under the optimized conditions of ultrasonic power of 550 W, extraction time of 26 min, and extraction temperature at 50°C, the highest yield of 13.47% ± 1.63% was obtained, which was in accordance with the predicted value of 13.71%. In comparison with traditional hot water extraction, the optimized UAE method significantly increased the extraction yield with lower extraction temperature and shorter extraction time. Furthermore, the in vitro antioxidant evaluation showed that EC 50 values of SNPS were 2.43 ± 0.21, 4.40 ± 0.35, and 0.56 ± 0.062 mg/mL for 2,2‐diphenyl‐1‐picrylhydrazyl radical (DPPH) radical, hydroxyl free radical, and 2,2’‐azinobis (3‐ethylbenzothiazoline‐6‐sulfonic acid) (ABTS) radical scavenging assay, respectively. The anti‐inflammatory potential of SNPS was detected in lipopolysaccharide (LPS) induced ICR mice. Real‐time reverse transcription‐polymerase chain reaction and enzyme‐linked immunosorbent assay showed that SNPS significantly improved LPS‐stimulated inflammatory response by decreasing mRNA and protein expression of interleukin (IL)‐6 and tumour necrosis factor (TNF)‐ α in a dose‐dependent manner. In conclusion, the extraction process of SNPS established in this study is reliable, and SNPS possesses potential antioxidant and anti‐inflammatory activities, which will provide a theoretical basis for guiding the clinical application of S. ningpoensis .
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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 | 0.000 |
| 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 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".