Polyphenols and Rosmarinic acid Contents, Antioxidant and Anti- Inflammatory Activities of Different Solvent Fractions from Nga- Mon (Perilla frutescens) Leaf
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Perilla is a rich source of polyphenols, which exhibits antioxidant, anti-inflammatory activities, and a variety of biological effects. The effect of differential solvents on the polyphenols, flavonoids, rosmarinic acid (RA), antiinflammatory and antioxidant activities of perilla leaf require investigation. In this study, perilla leaf was extracted with 70% ethanol and sequentially fractionated according to the solvent’s polarity with hexane, dichloromethane, ethyl acetate, and water. Samples were subjected to the bioactive compound measurements. The antioxidant and antiinflammation nature of perilla was analyzed based on the scavenging effects on DPPH•, ABTS•+, O2•- and nitric oxide (NO), as well as FRAP assay, and determination of the inhibition effects on NO, inducible nitric oxide synthase (iNOS), and cyclooxygenase-2 (COX-2) production in the cell-based study. The results indicate that among all different solvents used for sequential fractionation, ethyl acetate (EtOAc) was most effective in the separation of anti-oxidative and antiinflammatory compounds in the perilla leaf extract. These properties can partly be due to the presence of polyphenols, flavonoids, and also RA. It can be demonstrated here that, the perilla leaf EtOAc fraction could be used as a natural active pharmaceutical ingredient for dietary supplements and nutraceuticals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.000 | 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