Amino Acid Composition and Antioxidative Peptides from Protein Hydrolysates of Yellow Stripe Trevally ( <i>Selaroides leptolepis</i> )
Bibliographic record
Abstract
Hydrolysates from yellow stripe trevally meat with 15% degree of hydrolysis (DH) obtained using Alcalase (HA) and Flavourzyme (HF) following pH-stat method were characterized. Both hydrolysates, HA and HF, contained glutamic acid and glutamine as the major amino acids, while glycine was the dominant amino acid in fish flesh. Hydrolysates were also rich in aspartic acid, asparagine, alanine, lysine, and leucine. Essential amino acid/nonessential amino acid ratios were 0.55, 0.63, and 0.62 for flesh, HA, and HF, respectively. After separation on a Sephadex G-50 column, antioxidative activity of hydrolysate fractions was determined as Trolox equivalent antioxidant capacity. The fraction of HF with molecular weight (MW) of 1.77 kDa exhibited the strongest antioxidative activity, compared with other fractions. Among all fractions of HA, the one having a MW of 2.44 kDa showed the highest antioxidative activity. Thereafter, the selected Sephadex G-50 fractions from both HA and HF were further chromatographed using a Sephadex C-25 column, followed by HPLC. MW of antioxidative peptides from HA and HF determined by Maldi TOF/TOF was 656 and 617 Da, respectively. However, peptides isolated from both HA and HF possessed a lower antioxidative activity than Trolox at the same concentration (P < 0.05). HA and HF prevented DNA oxidative damage in Fenton reaction system tested by in vitro plasmid DNA relaxation assay. These results indicate that hydrolysates from yellow stripe trevally can be used as an important source of amino acids and serve as alternative natural antioxidants.
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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".