Purification of Peat Moss Extract Using a Supercritical CO<sub> 2</sub> and Verification of Its Biological Activities
Bibliographic record
Abstract
In this study, the canadian peat moss extract was purified by a supercritical 2 using three different conditions and assessed its biological activities. Peat moss was extracted by acid-alkaline extraction method (sample 1) and purified by a supercritical $CO_2$ at $40^{\circ}C$ under pressure of 100 bar (sample 2), 120 bar (sample 3) or 150 bar (sample 4). We evaluated the antioxidant activities of the samples by 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical-scavenging, $Fe^{2+}$ /ascorbate (FTC) and 2-thiobarbituric acid (TBA) methods. The antioxidant activities were examined by comparing the results with that of ascorbic acid as a positive control. Sample 3 showed relatively higher DPPH radical-scavenging activities than other samples. The antioxidant activity by FIC method exhibited similar results as the DPPH radical-scavenging activities. On the other hand, sample 2 showed higher antioxidant activity measured by TBA method of all. The whitening effects of the samples were examined using mushroom tyrosinase and B16F10 melanoma cells. Sample 3 exhibited overall significant whitening effects, however, other samples showed relatively lower effects. These results suggest that the peat moss extract purified by a supercritical 2 could be used as a cosmetic ingredient for the anti-aging and whitening effects.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".