Study of the Physico-chemical Properties and Antioxidant Activity of Extracted Melanins
Bibliographic record
Abstract
Ultraviolet (UV) light tends to cause skin damage; melanin can scavenge reactive oxygen species (ROS) produced from UV to protect skin from damage caused by free radicals. The purpose of this study was to investigate the physico-chemical properties and antioxidant activity of extracted melanins. Melanins were extracted from black tea (BT-melanin), black soybean (BS-melanin) and black-bone silky fowl (SF-melanin); they were then compared with synthetic melanin (SY-melanin). Three kinds of extracted melanins have absorbance ability in broad-spectrum (190-450 nm) wavelength. The experiment’s results indicated that the solubility in 25? water, organic solvents, 1 M NH4OH, and 1 M HCl of the three extracted melanins was similar to the solubility of synthetic melanin. The melanins also showed good stability in various light sources. The extracted melanins could chelate with Fe2+ and Cu2+. An in vitro study showed that the extracted melanin enhanced the survivability of fibroblast cells with 25 ?g mL-1 concentration after UV irradiation (254 nm, 0.09 mW cm2 -1) (p<0.05). All of the extracted melanins increased glutathione peroxidase (GSH-Px) and catalase activity when exposed to UV light (p<0.001). They inhibited the peroxidation of lipid (TBARS) and scavenged superoxide anion (p<0.001) induced by UV irradiation. According to the above results, the melanins extracted from black tea, black soybean, and black-bone silky fowl are similar in their physico-chemical properties, and they have the capacity for anti-oxidation and photoprotection from UV irradiation.
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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) | 0.000 | 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 | 0.000 |
| 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".