Evaluation of Antioxidant and Prooxidant Activities of Bamboo<i>Phyllostachys nigra</i>Var.<i>Henonis</i>Leaf Extract in Vitro
Bibliographic record
Abstract
Solvent-extracted bamboo leaf extract (BLE) containing chlorogenic acid, caffeic acid, and luteolin 7-glucoside was evaluated in vitro for free radical scavenging and antioxidant activities using a battery of test methods. BLE exhibited a concentration-dependent scavenging activity of DPPH radical. BLE prolonged the lag phase and suppressed the rate of propagation of liposome peroxidation initiated by peroxyl radical induced by 2,2'-azobis(2-amidinopropane dihydrochloride (AAPH) at 37 degrees C. BLE also prevented human low-density lipoprotein oxidation, mediated by Cu(2+), which was monitored by the lower formation of conjugated diene and fluorescence and a reduced negative charge of apo-B protein. Finally, BLE protected supercoiled DNA strand against scission induced by AAPH-mediated peroxyl radical. Prooxidant activity of BLE was seen in a Cu(2+)-induced peroxidation of structured phosphatidylcholine liposome, indicating catalytic peroxidation due to a relatively high reducing power of BLE. It was concluded that the BLE has both antioxidant activity and prooxidant activity; the antioxidant activity was attributed to free radical scavenging activity, and the prooxidant activity, albeit minor, resulted from the reducing power of plant phenolics in the presence of transitional metal ions.
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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 | 0.000 | 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 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".