Comparative Study on Antioxidant Activity of Vegetable Oils under in vitro and Cellular System
Bibliographic record
Abstract
Overproduction of free radical and oxidative stress are involved in the progression of degenerative disease. Therefore, to attenuate oxidative stress induced by free radical, natural antioxidants including vegetable oils with w-3 or w-6 fatty acids have been much concern. This study was to investigate the inhibitory effect against free radical and protective activity from oxidative stress of different vegetable oils as potential sources of antioxidants and linolenic acid. Olive, corn, and Perilla oil have free radical scavenging activity and protective effect from superoxide anion (O2-), and peroxynitrite (ONOO-)-induced cellular damage. In addition, Perilla oil exert the relatively high antioxidant effect at low concentration. Based on these results, we further studied radical scavenging effect of linolenic acid, which highly contained in Perilla oil. Our results revealed that linolenic acid increased 1,1-diphenyl-2-picrylhydrazyl and hydroxyl radical scavenging activity in a dose-dependent manner. Furthermore, linolenic acid showed noticeable protective effect against oxidative stress in a dose-dependent manner under LLC-PK1 cells. Thus, Perilla oil and linolenic acid as a major fatty acid from Perilla oil suppressed free radical production and protected from oxidative stress in O2- and ONOO--induced LLC-PK1 cells. The present study clearly demonstrated that linolenic acid is responsible for the radical scavenging effect against oxidative stress. Therefore, this research suggests the protective role of olive, corn, Perilla oil, and linolenic acid against free radical production and oxidative stress-related degenerative diseases.
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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 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".