Revisiting the Prospects of Plastein: Thermal and Simulated Gastric Stability in Relation to the Antioxidative Capacity of Casein Plastein
Bibliographic record
Abstract
Plastein, a product of protease-induced peptide aggregation, is thought to possess unique physical properties and bioactivity, although its formation, stability, and functional mechanisms remain unclear. This study demonstrates that plastein is formed from bovine casein peptides with Alcalase by hydrophobic and electrostatic interactions and less likely by covalent bonding. The peptide aggregation enhanced the Fe(III) reducing potential and decreased the Fe(II) chelating activity (p < 0.05) of casein peptides, but there was no difference in inhibition of Fe-induced linoleic acid peroxidation after plastein reaction. The casein plastein product retained its antioxidative activities after being heated at 100 °C. However, simulated gastric protease treatment with pepsin and pancreatic enzymes resulted in enhanced reducing potential and metal chelation of the casein plastein and reduction of the inhibitory effect on lipid peroxidation. It appears that the plasteins were disintegrated and further hydrolyzed by gastric proteases on the basis of the antioxidative capacity and RP-HPLC profile being similar to those of the casein hydrolysates. Therefore, plastein reaction may not confer metabolic stability or enhance the antioxidative capacity of casein peptides for prospective functional food applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 | 0.001 |
| 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".