Antioxidant activity and nutrient release from polyphenol-enriched cheese in a simulated gastrointestinal environment
Bibliographic record
Abstract
Green tea polyphenols are recognized for their antioxidant properties and their effects on lipid digestion kinetics. Polyphenols are sensitive to degradation in the intestinal environment. Interactions with dairy proteins could modulate the stability and biological activity of polyphenols during digestion. The objective of this study was to evaluate the release of nutrients (polyphenols, fatty acids and peptides) and the antioxidant activity in polyphenol-enriched cheese containing different levels of calcium in a simulated gastrointestinal environment. The relationship between cheese matrix texture, matrix degradation and nutrient release during digestion was also studied. Green tea extract was added to milk at 0% or 0.1%, and cheeses were produced on a laboratory scale. The level of available calcium was adjusted to low (Ca(low)), regular (Ca(reg)) or high (Ca(high)) during the salting step of the cheese-making process. Cheeses were subjected to simulated digestion. The rate and extent of fatty acid release were 21% lower for Ca(low) cheese than for Ca(reg) and Ca(high) cheeses. The greater adhesiveness of Ca(low) cheese, which resulted in lower rates of matrix degradation and proteolysis, contributed to the reduced rate of lipolysis. The presence of green tea extract in cheese reduced the release of free fatty acids at the end of digestion by 7%. The addition of green tea extract increased cheese hardness but did not influence matrix degradation or proteolysis profiles. The formation of complexes between tea polyphenols and proteins within the cheese matrix resulted in a more than twofold increase in polyphenol recovery in the intestinal phase compared with the control (tea polyphenol extract incubated with polyphenol-free cheese). Antioxidant activity was 14% higher in the digest from polyphenol-enriched cheese than in the control. These results suggest that cheese is an effective matrix for the controlled release of nutrients and for the protection of green tea polyphenol integrity and biological activity in the gastrointestinal environment.
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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 | 0.000 | 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 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".