Antioxidative activities of white rose flower extract and pharmaceutical advantages of its hexane fraction via free radical scavenging effects
Bibliographic record
Abstract
In this study, we determined the antioxidant activities of two different solvent fractions(butanol and hexane) obtained from white Rosa rugosa flowers by employing various assays such as 2,2-diphenyl-1-picrylhydrazyl hydrate (DPPH), 2,2'-azino-bis(3-ethylbenzthiazoline-6-sulfonic acid) (ABTS) radical scavenging activity, and nitric oxide (NO) scavenging and inhibition activity in S-nitroso-N-acetylpenicillamine (SNAP) in the RAW264.7 model. In addition, more advanced antioxidant assays were conducted, including lipid peroxidation, hydroxyl radical-mediated oxidation, DNA fragmentation, apoptosis, and cell growth. The results revealed that the hexane fraction, which contained a significant amount of polyphenols and volatile components, had excellent antioxidant potency and could scavenge free radicals of DPPH and ABTS. Interestingly, the hexane fraction inhibited lipid peroxidation to almost the same degree as a chemical antioxidant. In the NO assay, the hexane fraction effectively scavenged free radicals at all dose ranges and is expected to inhibit NO production in mammalian cells. The hexane fraction effectively prevented oxidative damage, which was induced by Cu2+/H2O2, to target proteins at lower concentrations (>1 microg x mL(-1)). The DNA fragmentation and the cell-level assays suggest that the hexane fraction may play a crucial role in inhibiting peroxynitrite and H2O2 attack. Based on the findings described in this study, the hexane fraction holds promise for use as a novel pharmaceutical antioxidant.
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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 | 0.000 | 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 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".