Tuning peptide self-assembly patterns in Tilapia scale gelatin hydrolysates through Cu2+ coordination: Characterization, identification and antioxidant evaluation
Bibliographic record
Abstract
We investigated the self-assembly pattern of Tilapia scale gelatin hydrolysates through Cu 2+ coordination and their in vivo antioxidant properties by Cu 2+ -induced oxidative stress using the Caenorhabditis elegans . Two treatments (Alcalase®, Alc; and Alcalase® followed by Flavourzyme®, Alc+Flav) were used to prepare whole and ≤ 1 kDa hydrolysates. Upon Cu 2+ coordination, the fibrillation and surface hydrophobicity of all hydrolysates decreased, suggesting a degradation of β-sheet structures and the formation of amorphous aggregates. Rheological studies confirmed that the structural and mechanical properties of the resulting supramolecular assemblies are tunable after Cu 2+ coordination. Due to the Cu 2+ -chelating and self-assembly properties, peptides present in the Alc hydrolysate significantly reduced endogenous ROS levels through Cu 2+ coordination, thereby extending the lifespan of C. elegans . The results provide valuable insights into the influence of Cu 2+ coordination on the progression of peptide self-assembly and Cu 2+ -induced oxidation in worms and prospects for food self-assembled peptides in biomaterial and nutraceutical applications. • His and Met-containing peptides contributed to the peptide-Cu 2+ complex formation. • Cu 2+ coordination by gelatin peptides demonstrated tunable self-assembled pattern. • The self-assembly and antioxidant properties of peptide-Cu 2+ complex were improved. • Fish gelatin hydrolysate could reduce oxidation in C. elegans by Cu 2+ coordination.
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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 | 0.001 | 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".