Isolation and Characterization of Antioxidative Peptides from Gelatin Hydrolysate of Alaska Pollack Skin
Bibliographic record
Abstract
Gelatin extracted from Alaska pollack skin was hydrolyzed with serial digestions in the order of Alcalase, Pronase E, and collagenase using a three-step recycling membrane reactor. The fraction from the second step, which was hydrolyzed with Pronase E, was composed of peptides ranging from 1.5 to 4.5 kDa and showed high antioxidative activity. Two different peptides showing strong antioxidative activity were isolated from the hydrolysate using consecutive chromatographic methods including gel filtration on a Sephadex G-25 column, ion-exchange chromatography on a SP-Sephadex C-25 column, and high-performance liquid chromatography on an ODS column. The isolated peptides, P1 and P2, were composed of 13 and 16 amino acid residues, respectively; and both peptides contained a Gly residue at the C-terminus and the repeating motif Gly-Pro-Hyp. The antioxidative activities of the purified peptides were measured using the thiobarbituric acid method, and the cell viability was measured with MTT assay. The results showed that P2 had potent antioxidative activity on peroxidation of linoleic acid. Moreover, the cell viability of cultured liver cells was significantly enhanced by addition of the peptide. These results indicate that the purified peptide, P2, from gelatin hydrolysate of Alaska pollack skin is a natural antioxidant which has potent antioxidative activity.
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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) | 0.001 | 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".